Dr. Robert Martí
Associate Professor at the Computer Vision and Robotics Group

   Grup de Visió per Computador i Robòtica
       Departament d'Arquitectura i Tecnologia de Computadors (ATC)
       Campus Montilivi - Edifici P-IV, Universitat de Girona
       17071 Girona, Spain.

   Phone: 00 34 972 418876 / fax: 00 34 972 418976

   robert.marti{at}udg.edu





Here is a list of my publications. Contact me in case you require a reprint or complete list of publications. Copyright and all rights in this material are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.


Publications


Journals

  1. [JMI23] M. Riveira-Martin, A. Rodríguez-Ruiz, R. Martí, M. Chevalier. Multi-vendor robustness analysis of a commercial artificial intelligence system for breast cancer detection,. J. Med. Imag. 10(5), 051807 (2023 [JCI 0.87, Q2]

  2. [MedPhys23] C Thomas, M Byra, R Marti, MH Yap, R Zwiggelaar BUS-Set: A benchmark for quantitative evaluation of breast ultrasound segmentation networks with public datasets,. Medical Physics, 2023. [IF 3.847, Q2 I & I]

  3. [Sens23] J Vidal, G Vallicrosa, R Martí, M Barnada Brickognize: Applying Photo-Realistic Image Synthesis for Lego Bricks Recognition with Limited Data,. Sensors 23 (4) 1898. [IF 3.847, Q2 I & I]

  4. [JAMA23] N. Konz; M. Buda; H. Gu; A. Saha; J. Yang; J. Chledowski; J. Park; J. Witowski; K. J. Geras; Y. Shoshan; F. Gilboa-Solomon; D. Khapun; V. Ratner; E. Barkan; M. Ozery-Flato; R. Martí; A. Omigbodun; C. Marasinou; N. Nakhaei; W. Hsu; P. Sahu; M. B. Hossain; J. Lee; C. Santos; A. Przelaskowski; J. Kalpathy-Cramer; B. Bearce; K. Cha; K. Farahani; N. Petrick; L. Hadjiiski; K. Drukker; S. G. Armato III; M. A. Mazurowski. A Competition, Benchmark, Code, and Data for Using Artificial Intelligence to Detect Lesions in Digital Breast Tomosynthesis,. JAMA Network Open 6 (2), e230524-e230524, 2023. [IF 13.37, Q1 MEDICINE]

  5. [LMS22] J. Puig, R. Martí, X. Lladó, MI Corral-Baqués and S. Sendrós-Tolsau Structural changes in subcutaneous and visceral abdominal fatty tissue induced by local application of 448 kHz capacitive resistive monopolar radiofrequency: a magnetic resonance imaging case study,. Lasers in Medical Science, accepted, 2022. [IF 2.557, Q2 100/211 SURGERY]

  6. [IMU22a] Md. Kamrul Hasan, Md. Ashraful Alam, Lavsen Dahal, Shidhartho Roy, Sifat Redwan Wahid, Md. Toufick E. Elahia, RobertMartí, Bishesh Khanal Challenges of deep learning methods for COVID-19 detection using public datasets,. Informatics in Medicine Unlocked, 30, 2022. [IF -]

  7. [IMU22b] Md. Kamrul Hasan, Md. Toufick E.Elahi, Md. Ashraful Alama, Md. Tasnim Jawada, R. Martí. DermoExpert: Skin lesion classification using a hybrid convolutional neural network through segmentation, transfer learning, and augmentation,. Informatics in Medicine Unlocked, 28, 2022. [IF -]

  8. [CBM22] R. Khaled, J. Vidal, JC. Vilanova, R. Martí A U-Net Ensemble for Breast Lesion Segmentation in DCE MRI,. Computers in Biology and Medicine, 140,105093, 2022. [IF 6.698 , Q1, 6/57 MATHEMATICAL & COMPUTATIONAL BIOLOGY]

  9. [Sen21] J. Vidal, C-Y. Lin, R. Martí Visual attention and color cues for 6D pose estimation on occluded scenarios using RGB-D data,. Sensors, 21(23), 2021. [Q2, 19/64 INSTRUMENTS AND INSTRUMENTATION]

  10. [NATMI21] Jungkyu Park, Yoel Shoshan, Robert Martí, Pablo Gómez del Campo, Vadim Ratner, Daniel Khapun, Aviad Zlotnick, Ella Barkan, Flora Gilboa-Solomon, Jakub Chledowski, Jan Witowski, Alexandra Millet, Eric Kim, Alana Lewin, Kristine Pysarenko, Sardius Chen, Julia Goldberg, Shalin Patel, Anastasia Plaunova, Melanie Wegener, Stacey Wolfson, Jiyon Lee, Sana Hava, Sindhoora Murthy, Linda Du, Sushma Gaddam, Ujas Parikh, Laura Heacock, Linda Moy, Beatriu Reig, Michal Rosen-Zvi and Krzysztof J Geras Lessons from the first DBTex Challenge,. Nature Machine Intelligence, 3, pages735–736 (2021) [IF 25.898, Q1, 1/144, COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE ]

  11. [RAD21] O.Díaz, A.Rodríguez-Ruiz, A.Gubern-Mérida, R.Martí and M.Chevalier ¿Son los sistemas de inteligencia artificial una herramienta útil para los programas de cribado de cáncer de mama? . Radiología (SERAM), Volume 63, Issue 3, May–June 2021, Pages 236-244. [IF --]

  12. [AIIM21] Md. Kamrul Hasan, Md. Ashraful Alam, Md. Toufick E Elahi, Shidhartho Roy, and Robert Marti DRNet: Segmentation and Localization of Optic Disc and Fovea from Diabetic Retinopathy Image. Artificial Intelligence in Medicine, vol 111, 102001, 2021. [IF 7.011, Q1 (8/31) Medical Informatics]

  13. [AIIM20] Moi Hoon Yap, Manu Goyal, Fatima Osman, Marti Robert, Erika Denton, Arne Juette, Reyer Zwiggelaar Breast Ultrasound Region of Interest Detection and Lesion Localisation. Artificial Intelligence in Medicine, 107,101880, 2020. [IF 4.383, Q1 (5/26) Medical Informatics]

  14. [CBM20a] Richa Agarwal, Oliver Díaz, Moi Hoon Yap, Xavier Lladó, Robert Martí Deep learning for mass detection in Full Field Digital Mammograms. Computers in Biology and Medicine, 121, 103774, 2020. [IF 3.434, Q1 (MATHEMATICAL AND COMPUTATIONAL BIOLOGY]

  15. [CBM20b] Md. Kamrul Hasan, MSc; Lavsen Dahal, MSc; Prasad N. Samarakoon, PhD; Fakrul Islam Tushar, MSc; Robert Marti, DSNet: Automatic Dermoscopic Skin Lesion Segmentation. Computers in Biology and Medicine, 120, 103738, 2020. [IF 3.434, Q1 (MATHEMATICAL AND COMPUTATIONAL BIOLOGY]]

  16. [MIA19] E.García, Y.Diez, O.Diaz, X.Lladó, A.Gubern-Mérida, R.Martí, J.Martí, and A.Oliver. Breast MRI and X-ray mammography registration using gradient values. Medical Image Analysis, 54, pp 76-87, 2019. [IF 11.148, Q1(5/133) CSAI]

  17. [JMI19] R. Agarwal, O.Diaz, X.Lladó, M.H. Yap, R. Martí Automatic mass detection in mammograms using deep convolutional neural networks. J. Med. Imag. 6(3) 031409, 2019. [CiteRank (Scopus) 1.75]

  18. [AIIM19] J. Bernal, K. Kushibar, D.S. Asfaw, S. Valverde, A. Oliver, R. Martí, X. Lladó, Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review. Artificial Intelligence in Medicine, 95, pp 64-81, 2019. [IF 4.383, Q1 (5/26) Medical Informaticssensor]

  19. [JMI18] M.H. Yap, M. Goyal, F. Osman, R. Marti, E. Denton, A. Juette, R. Zwiggelaar Breast ultrasound lesion recognition: end-to-end deep learning approaches. Journal of Medical Imaging (JMI), 6 (1), 011007, 2018. [CiteRank (Scopus) 1.75]

  20. [S18] Vidal, J.; Lin, C.-Y.; Lladó, X.; Martí, R. A Method for 6D Pose Estimation of Free-Form Rigid Objects Using Point Pair Features on Range Data.. Sensors, 18, 2678, 2018. [IF 3.031, Q1(15/61) I&I]

  21. [MP18] E.García, Y.Diez, O.Diaz, X.Lladó, R.Martí, J.Martí, and A.Oliver. A step-by-step review on patient-specific biomechanical finite elements models for breast MRI to X-ray mammography registration. Medical Physics, 45(1), pp e6-e31. 2018. [IF 3.177, Q2(32/129) CCIA]

  22. [UI18] R. Agarwal, O. Diaz, X. Lladó, A. Gubern-Merida, J. C. Vilanova, and R. Martí. Lesion Segmentation in Automated 3D breast Ultrasound: Volumetric Analysis. Ultrasonic Imaging, 40(2), pp. 97-112, 2018. [IF 2.490, Q2(9/31) Acoustics]

  23. [TMI18] E.García, Y.Diez, O.Diaz, X.Lladó, A.Gubern-Mérida, R.Martí, J.Martí, and A.Oliver. Multimodal breast parenchymal patterns correlation using a patient-specific biomechanical model. IEEE Trans. on Medical Imaging, 37(3), pp 712-723. 2018. [IF 7.816, Q1(3/106) CCIA]

  24. [JBHI18] M.H. Yap, G. Pons, J. Martí, S. Ganau, M. Sentís, R. Zwiggelaar, A.K. Davison and R. Martí Automated Breast Ultrasound Lesions Detection using Convolutional Neural Networks. IEEE Journal of Biomedical and Health Informatics, 22(4), pp. 1218-1226, 2018 [IF 4.217, Q1 (16/106) CSIA]

  25. [JBHI17] F. Velickovski, L. Ceccaroni, R. Marti, F. Burgos, C. Gistau, X. Alsina-Restoy, and J. Roca Automated spirometry quality assurance: supervised learning from multiple experts. IEEE Journal of Biomedical and Health Informatics, 22(1), 2017. [IF 3.850, Q1(18/148) CSIF]

  26. [EJR17] E.García, O.Diaz, R.Martí, Y.Diez, A.Gubern-Mérida, M.Sentís, J.Martí, and A.Oliver Local breast density assessment using reacquired mammographic images. European Journal of Radiology, 93, pp 121-127, 2017 [IF 2.843, Q2(38/128) RNMMI]

  27. [JMI16] J.Schwaab, Y.Diez, A.Oliver, R.Martí, J.van Zelst, A.Gubern-Mérida, A.Bensouda Mourri, J.Gregori, M.Günther. Automated quality assessment in 3D breast ultrasound images. Journal of Medical Imaging, 3(2), 027002. 2016. [CiteRank (Scopus) 1.26] -->

  28. [EJR16] A. Gubern-Mérida, S. Vreemann, R. Marti, J. Melendez, S. Lardenoije, R. M Mann, N. Karssemeijer, B. Platel. Automated detection of breast cancer in false-negative screening MRI studies from women at increased risk European Journal of Radiology,85(2), Pages 472–479 2016. [IF 2.462, Q2(44/127) RNMMI]

  29. [UI16] G. Pons, J. Martí, R. Martí, S. Ganau, A. Noble Breast Lesion Segmentation Combining B-mode and Elastography Ultrasound. Ultrasonic Imaging, 38 (3) pages 209-224, 2016. [IF 1.780, Q2(11/31)]

  30. [IJBC15] W.He, A.Juette, E.R.E.Denton, A.Oliver, R.Martí, and R.Zwiggelaar. A review on automatic mammography density and parenchymal segmentation. International Journal of Breast Cancer, Vol 2015, 2015.

  31. [CMB15] G. Lemaitre; R. Marti, J. Freixenet, JC. Vilanova, PM Walker, and F. Meriaudeau Computer-Aided Detection and Diagnosis for prostate cancer based on mono and multi-parametric MRI: A review. Computers in Biology and Medicine, 60, pages 8-31, 2015). [IF 1.521, Q2(39/86) B]

  32. [JDI15] A.Oliver, M.Tortajada, X.Lladó, J.Freixenet, S.Ganau, L.Tortajada, M.Vilagran, M.Sentís, and R.Martí Breast density analysis using an automatic density segmentation algorithm. Journal of Digital Imaging, 8(5), pp 604-612, 2015). [IF 1.406, Q3(91/124) RNMMI]

  33. [MIA15] A. Gubern-Mérida, R. Marti, J. Melendez, J. Hauth, R. Mann, N. Karssemeijer and B. Platel Automated localization of breast cancer in DCE-MRI. Medical Image Analysis, 20(1), pp 265-274, 2015). [IF 4.565, Q1(8/130) CSAI]

  34. [JBHI15] A. Gubern-Mérida, M. Kallenberg, R.M. Mann, R. Martí, N. Karssemeijer Breast segmentation and density estimation in breast MRI: a fully automatic framework. . IEEE Journal of Biomedical and Health Informatics, 19 (1), pp 349 - 357, 2015. [IF 2.093, Q1(29/144) COMPUTER SCIENCE, INFORMATION SYSTEMS]

  35. [CBM14] M.Tortajada, A.Oliver, R.Martí, S.Ganau, L.Tortajada, M.Sentís, J.Freixenet, and R.Zwiggelaar. Breast peripheral area correction in digital mammograms. Computers in Biology and Medicine, 50, pp 32-40, 2014. [IF 1.475, Q2(40/83) B]

  36. [UMB14] G. Pons, R. Martí, S. Ganau, M. Sentís, Joan Martí Computerized Detection of Breast Lesions using Deformable Part Models in Ultrasound Images . Ultrasound in Medicine and Biology, 40 (9), pp 2252-2264, 2014. [IF 2.214, Q1(5/31) ACOUSTICS]

  37. [P-ONE14] A. Gubern-Mérida, M. Kallenberg, B. Platel, R.M. Mann, R. Martí, N. Karssemeijer Volumetric breast density estimation from Full-Field Digital Mammograms: A validation study. . PLoS One, 9, pp e85952, 2014. [IF 3.234, Q1(9/57) MULTIDISCIPLINARY SCIENCES]

  38. [NINF14] Y.Diez, A.Oliver, M.Cabezas, S.Valverde, R.Martí, J.C.Vilanova, Ll.Ramió-Torrentà, À.Rovira, and X.Lladó. Intensity based methods for brain MRI longitudinal registration. A study on multiple sclerosis patients. Neuroinformatics, 12 (3), pp 365-379, 2014. [IF 3.136, Q1(12/100) CSIA]

  39. [MIA13] S.Ghose, A.Oliver, J.Mitra, R.Martí, X.Lladó, J.Freixenet, D.Sidibé, J.C.Vilanova, J.Comet, and F.Meriaudeau. A supervised learning framework of statistical shape and probability priors for automatic prostate segmentation in ultrasound images. Medical Image Analyis, 7(6), pp 587-600, 2013. [IF 4.087, Q1(7/115) CSAI]

  40. [JUM 2013] G. Pons, J.Martí, R.Martí, S. Ganau, J.C.Vilanova, J.A. Noble. Evaluating Lesion Segmentation in Breast Ultrasound Images Related to Lesion Typology. Journal of Ultrasound in Medicine, 32(9), pp 1659-70, 2013. [IF 1.245, Q2(14/30) ACOUSTICS]

  41. [MIA 2012] J.Mitra, Z.Kato, R.Martí, A.Oliver, X.Lladó, D.Sidibé, S.Ghose, J.C.Vilanova, J.Comet, and F.Meriaudeau. A spline-based diffeomorphism for prostate multimodal registration. Medical Image Analyis, 16(6), pp 1259-1279. 2012. [ [IF 4.087, Q1(7/115) CSAI]

  42. [CMPB 2012] S.Ghose, A.Oliver, R.Martí, X.Lladó, J.C.Vilanova, J.Freixenet, J.Mitra, D.Sidibé, and F.Meriaudeau. A survey of prostate segmentation methodologies in ultrasound, magnetic resonance, and computed tomography images. Computer Methods and Programs in Biomedicine, 108(1), pp 262-287. 2012. [IF 1.555, Q1(21/100) CSTM]

  43. [IJCARS 2012] S.Ghose, A.Oliver, R.Martí, X.Lladó, J.Freixenet, J.Mitra, J.C.Vilanova, J.Comet, and F.Meriaudeau. Statistical shape and texture model of quadrature phase information for prostate segmentation. International Journal of Computer Assisted Radiology and Surgery, 7(1), pp 43-55, 2012. [IF 1.364, Q3(76/120) RNMMI]

  44. [IJCARS 2012] J.Mitra, R.Martí, A.Oliver, X.Lladó, S.Ghose, J.C.Vilanova, and F.Meriaudeau. Prostate multimodality image registration based on b-splines and quadrature local energy. International Journal of Computer Assisted Radiology and Surgery, 7(3), pp 445-454. 2012. [IF 1.364, Q3(76/120) RNMMI]

  45. [NRAD12] X.Lladó, O.Ganiler, A.Oliver, R.Martí, J.Freixenet, L.Valls, J.C.Vilanova, Ll.Ramió-Torrentà, and A.Rovira. Automated detection of multiple sclerosis lesions in serial brain MRI. Neuroradiology, 54(8), pp 787-807. 2012. [IF 2.824, Q2(31/116) RNMMI]

  46. [TITB11] Y.Díez, A.Oliver, X.Lladó, J.Freixenet, J.Martí, J.C.Vilanova, and R.Martí. Revisiting intensity-based image registration appplied to mammography. IEEE Trans. on Information Technology in BioMedicine, 15(5), pp 716-725, 2011. [IF 1.676, Q1(27/133) CSIS]

  47. [AR10] A.Oliver, X.Lladó, J.Freixenet, R.Martí, E.Pérez, J.Pont, and R.Zwiggelaar Influence of using manual or automatic breast density information in a mass detection CAD system Academic Radiology, 17(7), pp 877-883, 2010. [IF 2.195, Q2(46/111) RNMMI]

  48. [CMIG09] X.Lladó, A.Oliver, J.Freixenet, R.Martí, J.Martí. A Textural Approach for Mass False Positive Reduction in Mammography Computerized Medical Imaging and Graphics, 33 (6), pp.415-422,2009. [IF 1.041, Q4(79/104) RNMMI]

  49. [MP08] J.Freixenet, A.Oliver, R.Martí, X.Lladó, J.Pont, E.Pérez, E.R.E.Denton, R.Zwiggelaar. Eigendetection of Masses considering False Positive Reduction and Breast Density Information. Medical Physics, 35(5):1840-53, 2008. [IF 3.871, Q1(13/92) RNMMI]

  50. [ULT08]R.Martí, J.Martí,J.Freixenet, R.Zwiggelaar, J.C.Vilanova, J.Barceló   Optimally Discriminant Moments for Speckle Detection in Real B-Scan Images Ultrasonics, 48(3):169-81, 2008. [IF 1.084, Q3(13/26) ]

  51. [TITB08] A.Oliver, J.Freixenet, R.Martí, J.Pont, E.Pérez, E.R.E.Denton, R.Zwiggelaar.   A Novel Breast Tissue Density Classification Methodology IEEE Trans. on Information Technology in BioMedicine, 12(1), pp 55-65, 2008. [IF 1.939, Q1(21/94) CSIA]

  52. [IVC07] A. Bosch, X. Muñoz and R. Martí A Review: Which is the best way to organize/classify images by content?, 25(6), pp. 778-791, June 2007. [IF 1.027, Q2(81/227) EEE]

  53. [CYB04] R. Marti, R. Zwiggelaar, C. Rubin and E. Denton 2D - 3D correspondence in mammography. Special Issue of the International Journal on Cybernetics & Systems, 35 (1), pp 85-105, 2004. [IF 0.768, Q2(7/18),CS&CYB ]

  54. [IJPRAI02] R. Marti, R. Zwiggelaar and C. Rubin Automatic point correspondence and registration based on linear structures. International Journal of Pattern Recognition and Artificial Intelligence, 16(3), pp. 331-340, 2002. [IF 0.359, Q3(51/74)]

  55. [EURASIP02] L. Blot, A. Davis, M. Holubinka, R. Marti and R. Zwiggelaar Automated quality assurance applied to mammographic imaging. EURASIP Journal on Applied Signal Processing 2002, 7, pp. 736-745, 2002. [IF 1.053, Q2(118/247), 2010.]

Patents

Abstracts in Journals


  1. [MS 2012] Y.Díez, X.Lladó, A.Oliver, R.Martí, E.Roura, M.Cabezas, O.Ganiler, J.Freixenet, J.C.Vilanova, L.Valls, Ll.Ramió-Torrentà, D.Pareto, and A.Rovira. Registration of serial brain MRI scans from multiple sclerosis patients. Analysis of 3D intensity-based methods. Multiple Sclerosis, . [IF 4.255, Q1(27/191) CN Medical Abstract]

  2. [IJCARS 2011] J.Mitra, F.Meriaudeau, R.Martí, A.Oliver, X.Lladó, S.Ghose, and J.C.Vilanova. Quadrature filter enhanced b-spline registration applied to prostate multimodal images. International Journal of Computer Assisted Radiology and Surgery, 6(s1), pp 323-324, 2011. [IF 1.481, Q2(89/198) S]

  3. [IJCARS 2011] S.Ghose, A.Oliver, R.Martí, X.Lladó, J.Freixenet, J.C.Vilanova, F.Meriaudeau, and J.Mitra. Quadrature phase-based statistical shape and appearance for prostate segmentation. International Journal of Computer Assisted Radiology and Surgery, 6(s1), pp 12-13, 2011. [IF 1.481, Q2(89/198) S]


  4. [IJCARS 2008] A.Oliver, J.Freixenet, X.Lladó, R.Martí, J.Pont, E.Pérez, and R.Zwiggelaar. Comparing the performance of a mass detection CAD system when using manual and automatic breast density information. International Journal of Computer Assisted Radiology and Surgery, 3(s1), pp 420-421, 2008.

  5. [IJCARS 2008] R.Martí, J.Martí, J.Freixenet, J.C.Vilanova, J.Barceló, A.Gubern, A.Oliver, and X.Lladó. Intensity based MRI/TRUS data fusion for prostatic guided biopsy. International Journal of Computer Assisted Radiology and Surgery, 3(s1), pp 369-370, 2008.

  6. [IJCARS 2007] J.Freixenet, A.Oliver, X.Lladó, R.Martí, and J.Martí. Mass Eigendetection and the Benefits of Introducing Breast Density Information International Journal of Computer Assisted Radiology and Surgery, 2(s1), pp 332-334, 2007.


Book Chapters


  1. [AIM21] Agarwal R., Yap M.H., Hasan M.K., Zwiggelaar R., Martí R. Deep Learning in Mammography Breast Cancer Detection. In: Lidströmer N., Ashrafian H. (eds) Artificial Intelligence in Medicine. Springer, Cham. https://doi.org/10.1007/978-3-030-58080-3_157-1.

  2. [CRC2018] G. Lemaitre, R.Martí and F. Meriaudeau Computer Aided Diagnosis Systems for Prostate Cancer Detection: Challenges and Methodologies. . Chapter 10 in Prostate Cancer Imaging: An Engineering and Clinical Perspective. pp. 87-164, CRC Press, ISBN: 978-1-4987-8623-2, 2018.

  3. [IWDM 2010] J.Martí, A.Oliver, J.Freixenet, R.Martí. Digital Mammography, Proceedings of the 10th International Workshop. Lecture Notes in Computer Science, vol 6136. 2010.

  4. [BEN10] J. Martí, A. Gubern-Mérida, J. Massich, A. Oliver, J.C. Vilanova, J. Comet, E. Pérez, M. Arzoz, R. Martí Ultrasound Image Analysis. Methods and Applications Recent Advances in Biomedical Signal Processing. Editors Juan M. Górriz, Elmar W. Lang and Javier Ramírez. Bentham Science Publishers, 2010.

  5. [SPIE06] R. Marti, C. Rubin, E. Denton and R. Zwiggelaar. A Mammographic Registration Framework Based On Anatomical Linear Structures. Recent Advances in Breast Imaging, Mammography and Computer-Aided Diagnosis of Breast Cancer. Editors J. Suri And R. M. Rangayyan. Spie Press, Vol. PM155, pp 493/534. 2006. ISBN: 0-8194-6081-8.

Invited talks


  1. [SMIT 2012] R. Martí.Research in CAD for Breast Cancer. Recent Advances and Experiences. 24th International Conference of the Society for Medical Innovation and Technology (SMIT), Barcelona, 2012.

  2. [SEDIM 2011] J. Freixenet and R. Martí. Avances en CAD mamográfico y ecográfico. ¿Inteligencia artificial?. XII Congreso Nacional de la Sociedad Española de Diagnóstico por la Imagen de la Mama, Marbella, 2011.

  3. [SCU 2006] M. Arzoz and R. Martí. ProSCAN: Sistema d’ajuda a la localització del càncer de pròstata mitjançant la integració de la imatge de ressonància magnètica i ecografia . XII Simposi de la Societat Catalana d'Urologia, Girona 2006.

PhD Thesis

International Conferences


  1. [IWBI22a] J Vidal, R Martí Using deep learning for triple-negative breast cancer classification in DCE-MRI 16th International Workshop on Breast Imaging (IWBI2022) 12286, 222-227, 2022

  2. [IWBI22b] E García, R Martí, J Martí, J del Riego, C Aynes, A Oliver, O Diaz Simultaneous pectoral muscle and nipple location in MLO mammograms, considering image quality assumptions 16th International Workshop on Breast Imaging (IWBI2022) 12286, 83-89 2022

  3. [IWBI22c] R Martí, PG del Campo, J Vidal, X Cufí, J Martí, M Chevalier, J Freixenet Lesion detection in digital breast tomosynthesis: method, experiences and results of participating to the DBTex challenge 16th International Workshop on Breast Imaging (IWBI2022) 12286, 216-221, 2022

  4. [ICPR21] Roa'A Khaled, Joel Vidal and Robert Martí Deep Learning Based Segmentation of Breast Lesions in DCE-MRI Workshop on Artificial Intelligence for Healthcare Applications, ICPR 2020. LNCS.

  5. [IWBI20a] B. Alyafi, O. Díaz, JC. Vilanova, J. del Riego, R. Martí, Quality analysis of DCGAN-generated mammography lesions International Workshop on Breast Imaging, Leuven, 2020.

  6. [IWBI20b] E. García, Y. Díez, A. Oliver, N. Karssemeijer, J. Martí, R. Martí, and O. Díaz Evaluation of elastic parameters for breast compression using a MRI-mammography registration approach International Workshop on Breast Imaging, Leuven, 2020.

  7. [IWBI20c] E. García, C. Fedon, M. Caballo, R. Martí, I. Sechopoulos, and O. Díaz Realistic compressed breast phantoms for medical physics applications International Workshop on Breast Imaging, Leuven, 2020.

  8. [SPIE20] B. Alyafi, O. Díaz, R. Martí, DCGANs for Realistic Breast Mass Augmentation in X-ray Mammography SPIE Medical Imaging, Houston, 2020.

  9. [ICCAR18] J. Vidal, C. Lin, R. Martí 6D Pose Estimation using an Improved Method based on Point Pair Features IEEE ICCAR 2018 Conference, Auckland, New Zealand

  10. [IWBI18a] E. García, A. Oliver, O. Diaz, Y. Díez, A. Gubern-Mérida, J. Martí, R. Martí Changes in breast density over time using automatic density measures: preliminary analysis. 14th International Workshop on Breast Imaging (IWBI). July 2018, Atlanta, USA

  11. [IWBI18b] R. Agarwal, O. Diaz, X. Lladó, R. Marti. Mass detection in mammograms using pre-trained deep learning models. 14th International Workshop on Breast Imaging (IWBI). July 2018, Atlanta, USA

  12. [IWBI18c] A. Malet, D. Garcia-Pinto, J. Fernandez, R. Marti, O. Diaz. Breast Tomosynthesis reconstruction using software tool TIGRE. 14th International Workshop on Breast Imaging (IWBI). July 2018, Atlanta, USA

  13. [SPIE18] M.H. Yap, M. Goyal, F. Osman, E. Ahmad, R. Martí, E. Denton, A. Juette, R. Zwiggelaar End-to-end breast ultrasound lesions recognition with a deep learning approach. Proc. SPIE 10578, Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging, 1057819

  14. [IWBI18d] G. Trovini, C. Napoli, R. Marti, A. Martin, A. Bria, C. Marrocco, M. Molinara, F. Tortorella, O. Diaz. A deep learning framework for micro-calcification detection in 2D mammography and C-view. . 14th International Workshop on Breast Imaging (IWBI). July 2018, Atlanta, USA

  15. [ICCVW17] J. Vidal, C. Lin, R. Martí 6D Pose Estimation Challenge Using Improved Point Pair Features 3rd International Workshop on Recovering 6D Object Pose Organized, ICCV 2017 - October 29th, Venice, Italy

  16. [IBPRIA17] E. García, A. Oliver, Y. Díez, O. Diaz, X. Llado, R. Martí and J. Marti Similarity metrics for intensity-based registration using breast density maps In Pattern Recognition and Image Analysis, LNCS vol. 10255, pp. 217-225

  17. [EMBC 2017] G Lemaitre, R Martí, M Rastgoo, F Mériaudeau. Computer-Aided Detection for Prostate Cancer Detection based on Multi-Parametric Magnetic Resonance Imaging . EMBC 2017 : 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Jul 2017, Jeju Island, South Korea

  18. [ECR 2017] R.Agarwal, O.Díaz, Y. Díez A.Gubern-Mérida, J.C. Vilanova, R.Martí. A clinical tool for temporal analysis in 3D automated breast ultrasound. ECR, European Congress of Radiology, oral presentation, Vienna, Austria, 2017. Abstract.

  19. [SPIE 2017] E.García, A.Oliver, O.Diaz, Y.Diez, R.Martí, and J.Martí. Mapping 3D breast lesions from full-field digital mammograms using subject-specific finite element models. SPIE Conference on Medical Imaging, 1013504-1013504-8. Orlando, Florida. February 2017.

  20. [SPIE 2017] O.Diaz, E.García, A.Oliver, J.Martí, and R.Martí. Scattered radiation in DBT geometries with flexible breast compression paddles: a Monte Carlo simulation study. SPIE Conference on Medical Imaging, 101324G-101324G-7. Orlando, Florida. February 2017.

  21. [ECR16a] O. Diaz, R. Agarwal, A. Gubern-Merida, J. van Zelst, Y. Diez, R. Martí R. Automated volumetric lesion quantification in automated 3D breast ultrasound: comparison of 5 breast lesion segmentation algorithms. ECR, European Congress of Radiology, poster presentation, Vienna, Austria, 2016. Abstract (SS 1805), B-1137.

  22. [ECR16b] Schwaab J., Malavé Dos Santos A., Diez Y., Martí R., van Zelst J., Bensouda Mourri A., Gregori J., Günther M. Computerised image quality assessment in automated 3D breast ultrasound images. ECR, European Congress of Radiology, poster presentation, Vienna, Austria, 2016. Abstract (SS 1805), B-1138

  23. [ECR16c] Y. Diez, A. Maroto González, O. Diaz, A. Gubern-Merida, R. Martí A study of rigid registration methods for ABUS temporal studies . ECR, European Congress of Radiology, poster presentation, Vienna, Austria, 2016.

  24. [IWDM16] O.Diaz, A.Oliver, S.Ganau, J.Martí, M.Sentís, and R.Martí. Feasibility of depth sensors to study breast deformation during mammography procedures. International Workshop on Breast Imaging, LNCS 9699, pp 446-453. Malmö, Sweden. June 2016.

  25. [SPIE16] G. Lemaitre, M. Rastgoo, J. Massich, J. C. Vilanova, P. M. Walker, J. Freixenet, A. Meyer-Baese, F. Meriaudeau, and R. Marti. Normalization of T2W-MRI prostate images using Rician a priori. SPIE Medical Imaging 2016. San Diego: USA (February 2016)

  26. [BIA15] E.García, A.Oliver, Y.Diez, O.Diaz, J.Georgii, A.Gubern-Mérida, R.Martí, and J.Martí. Comparing regional breast density using full-field digital mammograms and magnetic resonance imaging: a preliminary study. MICCAI Workshop on Breast Image Analysis, pp 33-40. Munich, Germany. October 2015.

  27. [RSNA15] A. Gubern-Mérida, S. Vreemann, R. Marti, J. Melendez, R.M. Mann, B. Platel and N. Karssemeijer. Automated Detection of Mass-like, Non-mass-like and Focus Breast Cancer Lesions Visible in False-negative Screening DCE-MRI. Annual Meeting of the Radiological Society of North America, 2015.

  28. [QCAV15] G. Lemaitre, J. Massich, R. Marti, J. Freixenet, J. C. Vilanova, P. M. Walker, D. Sidibe, and F. Meriaudeau. A Boosting Approach for Prostate Cancer Detection using Multi-parametric MRI. International Conference on Quality Control and Artificial Vision (QCAV) 2015. Le Creusot: France (June 2015).

  29. [ECR15] A. Gubern-Mérida, S. Vreemann, R. Martí, J. Melendez, S.A. Lardenoije, R.M Mann, B. Platel, N. Karssemeijer. Automated Detection of Breast Cancer to Aid with the Interpretation of High Risk Screening DCE-MRI. ECR, European Congress of Radiology, oral presentation, Vienna, Austria, 2015. Abstract

  30. [IWDM14a] R.Martí, Y.Diez, A.Oliver, M.Tortajada, R.Zwiggelaar, and X.Lladó. Detecting abnormal mammographic cases in temporal studies using image registration features. International Workshop on Breast Imaging, LNCS 8539, pp 612-619. Gifu, Japan. July 2014.

  31. [IWDM14b] Y. Díez, A. Gubern-Mérida, L. Wang, S. Diekmann, J. Martí, B. Platel, J. Kramme, R. Martí. Comparison of Methods for Current-to-Prior Registration of Breast DCE-MRI. International Workshop on Breast Imaging, LNCS 8539, pp 689-695. Gifu, Japan. July 2014.

  32. [IWDM14c] J.Massich, F.Meriaudeau, M.Sentís, S.Ganau, E.Pérez, D.Puig, R.Martí, A.Oliver, and J.Martí. SIFT texture description for understanding breast ultrasound images. International Workshop on Breast Imaging, LNCS 8539, pp 681-688. Gifu, Japan. July 2014.
  33. [BIA13] A. Gubern-Mérida, B. Platel, R. M. Mann, R. Martí and N. Karssemeijer. Automated localization of malignant lesions in breast DCE-MRI, in: MICCAI Workshop: Breast Image Analysis, 2013.

  34. [SPIE13] A. Gubern-Mérida, L. Wang, M. Kallenberg, R. Martí, Horst K. Hahn and N. Karssemeijer. Breast segmentation in MRI: quantitative evaluation of three methods . SPIE Medical Imaging, Florida,2013.

  35. [IbPRIA13a] S. Widiyanto, X. Cufí, M. Rubio, I. Muñoz, E. Fulladosa and R. Martí Automatic Intra Muscular Fat Analysis on Dry-Cured Ham Slices Iberian Conference on Pattern Recognition and Image Analysis 2013, LNCS 7887, pages 873-880.

  36. [IbPRIA13b] Y. Díez, M. Tortajada, S. Ganau, L. Tortajada, M. Sentís and R. Martí. Demons Methods for Digital Mammography Registration. Iberian Conference on Pattern Recognition and Image Analysis 2013, LNCS 7887, pages 253-260.

  37. [IbPRIA13b] G. Pons, R. Martí, S. Ganau, M. Sentís and J. Martí. Feasibility Study of Lesion Detection Using Deformable Part Models in Breast Ultrasound Images. Iberian Conference on Pattern Recognition and Image Analysis 2013, LNCS 7887, pages 269-276.

  38. [MICCAI 2012] A. Gubern-Mérida, M. Kallenberg, R. Martí and N. Karssemeijer. Segmentation of the pectoral muscle in breast MRI using atlas-based approaches. MICCAI 2012, Lecture Notes in Computer Science, 2012, Volume 7511/2012, 371-378

  39. [ICPR 2012] S.Ghose, J.Mitra, A.Oliver, R.Martí, X.Lladó, J.Freixenet, J.C.Vilanova, D.Sidibé, and F.Meriaudeau. A Mumford-Shah functional based variational model with contour, shape and probability prior information for prostate segmentation. International Conference on Pattern Recognition. Tsukuba Science City, Japan. November 2012.

  40. [ICPR 2012] S.Ghose, J.Mitra, A.Oliver, R.Martí, X.Lladó, J.Freixenet, J.C.Vilanova, D.Sidibé, and F.Meriaudeau. Graph cut energy minimization in a probabilistic learning framework for 3D prostate segmentation in MRI. International Conference on Pattern Recognition. Tsukuba Science City, Japan. November 2012.

  41. [ICPR 2012] J.Mitra, Z.Kato, S.Ghose, D.Sidibé, R.Martí, X.Lladó, A.Oliver, J.C.Vilanova, and F.Meriaudeau. Spectral clustering to model deformations for fast multimodal registration. International Conference on Pattern Recognition. Tsukuba Science City, Japan. November 2012.

  42. [MICCAI-GC 2012] S.Ghose, J.Mitra, A.Oliver, R.Martí, X.Lladó, J.Freixenet, J.C.Vilanova, D.Sidibé, and F.Meriaudeau. A stochastic approach to prostate segmentation in MRI. MICCAI Grand Challenge: Prostate MR image segmentation. Nice, France. October 2012.

  43. [ICIP 2012] J.Mitra, S.Ghose, D.Sidibé, A.Oliver, R.Martí, X.Lladó, J.C.Vilanova, J.Comet, and F.Meriaudeau. Weighted likelihood function of multiple statistical parameters to retrieve 2D TRUS-MR slice correspondence for prostate biopsy. IEEE International Conference on Image Processing. Orlando, Florida. October 2012.

  44. [ICIP 2012] S.Ghose, J.Mitra, A.Oliver, R.Martí, X.Lladó, J.Freixenet, J.C.Vilanova, D.Sidibé, and F.Meriaudeau. A coupled schema of probabilistic atlas and statistical shape and appearance model for 3D prostate segmentation in MR images. IEEE International Conference on Image Processing. Orlando, Florida. October 2012.

  45. [BP 2012] R.Martí, A.Oliver, X.Lladó, X.Cufí, J.Martí, J.Freixenet, J.Salvi. VIBOT Day: un exemple de bones pràctiques universitat-empresa. Jornades de Bones Pràctiques. Girona, Spain. September 2012.

  46. [ACIVS 2012] S.Ghose, J.Mitra, A.Oliver, R.Martí, X.Lladó, J.Freixenet, J.C.Vilanova, D.Sidibé, and F.Meriaudeau. A supervised learning framework for automatic prostate segmentation in transrectal ultrsound images. Advanced Concepts for Intelligent Vision Systems, LNCS 7517, pp 190-200. Brno, Czech Republic. September 2012.

  47. [EMBC 2012] J.Mitra, S.Ghose, D.Sidibé, R.Martí, A.Oliver, X.Lladó, J.C.Vilanova, J.Comet, and F.Meriaudeau. Joint probability of shape and image similarities to retrieve 2D TRUS-MR slice correspondence for prostate biopsy. IEEE Conference of the Engineering in Medicine and Biology Society. San Diego, California. August 2012.

  48. [EMBC 2012] S.Ghose, J.Mitra, A.Oliver, R.Martí, X.Lladó, J.Freixenet, J.C.Vilanova, J.Comet, D.Sidibé, and F.Meriaudeau. Spectral clustering of shape and probability prior model for automatic prostate segmentation in ultrasound images. IEEE Conference of the Engineering in Medicine and Biology Society. San Diego, California. August 2012.

  49. [IWDM 2012] M.Tortajada, A.Oliver, R.Martí, M.Vilagran, S.Ganau, L.Tortajada, M.Sentís, and J.Freixenet. Adapting breast density classification from digitized to full-field digital mammograms. International Workshop on Digital Mammography, LNCS 7361, pp 561-568. Philadelphia, Pennsylvania. July 2012.

  50. [IWDM 2012] J.Massich, F.Meriaudeau, M.Sentís, S.Ganau, E.Pérez, R.Martí, A.Oliver, and J.Martí. Automatic seed placement for breast lesion segmentation on US images. International Workshop on Digital Mammography, LNCS 7361, pp 308-315. Philadelphia, Pennsylvania. July 2012.

  51. [SPIE12a] G. Pons, J. Martí, R. Martí, M. Cabezas, A. Di Battista, J.A. Noble Lesion segmentation and bias correction in breast ultrasound B-mode images including elastography information. SPIE Conference on Medical Imaging, San Diego, California, February 2012.

  52. [SPIE12b] J. Mitra, A. Srikantha, D. Sidibe, R. Martí, A. Oliver, X. Lladó, S. Ghose, J.C. Vilanova, J. Comet, F. Meriaudeau. A shape-based statistical method to retrieve 2D TRUS-MR slice correspondence for prostate biopsy. SPIE Conference on Medical Imaging, San Diego, California, February 2012.

  53. [SPIE12c] S. Ghose, A. Oliver, R. Martí, X. Lladó, J. Freixenet, J. Mitra, J.C. Vilanova, F. Meriaudeau, A hybrid framework of multiple active appearance models and global registration for 3D prostate segmentation in MRI.. SPIE Conference on Medical Imaging, San Diego, California, February 2012.

  54. [MICCAI_PC11a] S.Ghose, A.Oliver, R.Martí, X.Lladó, J.Freixenet, J.Mitra, J.C.Vilanova, J.Comet, and F.Meriaudeau Multiple mean models of statistical shape and probability priors for automatic prostate segmentation. MICCAI Workshop on Prostate Cancer Imaging: Computer Aided Diagnosis, Prognosis, and Intervention, LNCS 6963, pp 35-46. Toronto, Canada. September 2011

  55. [MICCAI_BIA11a] A. Gubern-Mérida, M. Kallenberg, R. Martí and N. Karssemeijer Fully automatic fibroglandular tissue segmentation in breast MRI: an atlas-based approach. MICCAI Workshop on Breast Image Analysis. Toronto, Canada. September 2011

  56. [MICCAI_BIA11b] J.Massich, F.Meriaudeau, E.Pérez, R.Martí, A.Oliver, and J.Martí Seed selection criteria for breast lesion segmentation in ultra-sound images. MICCAI Workshop on Breast Image Analysis. Toronto, Canada. September 2011

  57. [ICIP11] S.Ghose, A.Oliver, R.Martí, X.Lladó, J.Freixenet, J.C.Vilanova, and F.Meriaudeau. A probabilistic framework for automatic prostate segmentation with a statistical model of shape and appearance. IEEE International Conference on Image Processing, pp 725-728. Brussels, Belgium. September 2011.

  58. [DICTA11a] J.Mitra, Z.Kato, R.Martí, A.Oliver, X.Lladó, S.Ghose, J.C.Vilanova, and F.Meriaudeau. A non-linear diffeomorphic framework for prostate multimodal registration. International Conference on Digital Image Computing: Techniques and Applications. Noosa, Australia. December 2011

  59. [DICTA11b] S.Ghose, A.Oliver, R.Martí, X.Lladó, J.Freixenet, J.Mitra, J.C.Vilanova, J.Comet, and F.Meriaudeau. Statistical shape and probability prior model for automatic prostate segmentation. International Conference on Digital Image Computing: Techniques and Applications. Noosa, Australia. December 2011

  60. [IBPRIA11a] G. Pons, J. Martí, R. Martí and J.A. Noble Simultaneous Lesion Segmentation and Bias Correction in Breast Ultrasound Images. Iberian Conference on Pattern Recognition and Image Analysis, LNCS 6669, pp. 692-699, 2011.

  61. [IBPRIA11b] A. Gubern-Mérida, R. Martí, M. Kallenberg and N. Karssemeijer Multi-class probabilistic atlas-based segmentation method in breast MRI. Iberian Conference on Pattern Recognition and Image Analysis,LNCS 6669, pp. 660-667 2011.

  62. [CARS11a] J.Mitra, F.Meriadeau, R.Martí, A.Oliver, X.Lladó, S.Ghose, and J.C.Vilanova. Quadrature filter enhanced b-spline registration applied to prostate multimodal images. Computer Assisted Radiology and Surgery. Berlin, Germany. June 2011.

  63. [CARS11b] S.Ghose, A.Oliver, R.Martí, X.Lladó, J.Freixenet, J.C.Vilanova, F.Meriaudeau, and J.Mitra. Quadrature phase-based statistical shape and appearance for prostate segmentation. Computer Assisted Radiology and Surgery. Berlin, Germany. June 2011.

  64. [SPIE11a] J.Mitra, R.Martí, A.Oliver, X.Lladó, J.C.Vilanova, and F.Meriaudeau. A comparison of thin-plate splines with automatic correspondences and b-splines with uniform grids for multimodal prostate registration. SPIE Conference on Medical Imaging. Lake Buena Vista, Orlando, Florida. February 2011.

  65. [SPIE11b] S.Ghose, A.Oliver, R.Martí, X.Lladó, J.Freixenet, J.C.Vilanova, and F.Meriaudeau. Prostate segmentation with local binary patterns guided active appearance model. SPIE Conference on Medical Imaging. Lake Buena Vista, Orlando, Florida. February 2011.

  66. [SITIS10a] J.Mitra, A.Oliver, R.Martí, X.Lladó, J.C.Vilanova, and F.Meriaudeau. A thin-plate spline based multimodal prostate registration with optimal correspondences. International Conference on Signal-Image Technology & Internet-Based Systems, pp 7-11. Kuala Lumpur, Malaysia. December 2010.

  67. [SITIS10b] S.Ghose, A.Oliver, R.Martí, X.Lladó, J.Freixenet, J.C.Vilanova, and F.Meriaudeau. Prostate segmentation with texture enhanced Active Appearance Model. International Conference on Signal-Image Technology & Internet-Based Systems, pp 18-22. Kuala Lumpur, Malaysia. December 2010.

  68. [DICTA10] J.Mitra, A.Oliver, R.Martí, X.Lladó, J.C.Vilanova, and F.Meriadeau. Multimodal prostate registration using thin-plate splines from automatic correspondences. International Conference on Digital Image Computing: Techniques and Applications, pp 587-592. Sydney, Australia. December 2010.

  69. [RSNA10] M.Tortajada, A.Oliver, Y.Díez, R.Martí, J.C.Vilanova, and J.Freixenet Integrating Bilateral Information in the Eigendetection CAD Approach. Scientific Assembly and Annual Meeting of the Radiological Society of North America. Chicago, Illinois. November 2010

  70. [MICCAIW10] S.Ghose, A.Oliver, R.Martí, X.Lladó, J.Freixenet, J.C.Vilanova, and F.Meriaudeau Texture guided Active Appearance Model propagation for prostate segmentation. MICCAI Workshop on Prostate Cancer Imaging: Computer Aided Diagnosis, Prognosis, and Intervention, LNCS 6367, pp 111-120. Beijing, China. September 2010.

  71. [EMBC10] M.Tortajada, A.Oliver, Y.Díez, R.Martí, J.C.Vilanova, and J.Freixenet Improving a CAD system using bilateral information. IEEE Engineering in Medicine and Biology Society Conference. Buenos Aires, Argentina. September 2010

  72. [ICIP10a] R. Martí and A. Noble Elastic Modulus Imaging using Optical Flow and Image Registration. IEEE International Conference on Image Processing (ICIP), pp 605-608. Hong Kong. September 2010.

  73. [ICIP10b] Y. Díez, A. Oliver, X. Lladó and R. Martí Comparison of Registration Methods Using Mammographic Images IEEE International Conference on Image Processing (ICIP), pp 4421-4424. Hong Kong. September 2010.

  74. [ICIP10c] A.Torrent, A.Oliver, X.Lladó, R.Martí and J.Freixenet. A supervised micro-calcification detection approach in digitised mammograms IEEE International Conference on Image Processing (ICIP), pp 4345-4348. Hong Kong. September 2010.

  75. [IWDM10]J.Massich, F.Meriaudeau, E.Pérez, R.Martí, A.Oliver, and J.Martí Lesion segmentation in breast sonography International Workshop on Digital Mammography, LNCS 6136, pp 39-45. Girona, Spain. June 2010

  76. [MICCAIW09]A. Gubern-Merida and R. Martí Atlas Based Segmentation of the prostate in MR images International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI): Segmentation Challenge Workshop, London, 2009.

  77. [ICERI09]R. Martí, X. Cufí and J. Salvi Erasmus Mundus European Master in Vision and Robotics (VIBOT): Experiences, Present and Future International Conference of Education, Research and Innovation (ICERI), Madrid 2009.

  78. [RSNA08]R. Martí, J.C. Vilanova, J. Freixenet, J. Barceló, M. Arzoz and J. Martí Automatic Method for the Detection of Fully Developed Speckle Patterns in B-scan Images to Perform a 3D Reconstruction Using Only Image Content Information from Freehand Sensorless ImagesRadiological Society of North America (RSNA), pp 309, Chicago, 2008. 2008.

  79. [IWDM08a] A.Torrent, A.Bardera, A.Oliver, J.Freixenet, I.Boada, M.Feixas, R.Martí, X.Lladó, J.Pont, E.Pérez, S.Pedraza, and J.Martí Breast density segmentation: a comparison of clustering and region based techniques.International Workshop on Digital Mammography, Tucson, Arizona. LNCS 5116/2008, pp 9-16. 2008.

  80. [IWDM08b] M. Tortajada, R. Martí, J. Freixenet, M. Sentís and J. Fernández Image Correction and Reconstruction for Breast Biopsy International Workshop on Digital Mammography. Tucson, Arizona. LNCS 5116/2008, pp 545-552 2008.

  81. [CARS08a] R.Martí, J.Martí, J.Freixenet, J.C.Vilanova, J.Barceló, A.Gubern, A.Oliver, and X.Lladó Intensity based MRI/TRUS data fusion for prostatic guided biopsy. Computer Assisted Radiology and Surgery. Barcelona, Spain, June 2008

  82. [CARS08b] A.Oliver, J.Freixenet, X.Lladó, R.Martí, J.Pont, E.Pérez, R.Zwiggelaar Comparing the performance of a mass detection CAD system when using manual and automatic breast density information. Computer Assisted Radiology and Surgery. Barcelona, Spain, June 2008

  83. [IbPRIA07a] R. Martí, J. Martí, J. Freixenet, J.C. Vilanova, J. Barceló Optimally Discriminant Moments for Speckle Detection in Real B-Scan Images. 3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA'07). LNCS 4478, pp. 242-249. Girona. 2007

  84. [IbPRIA07b] R. Martí, A. Oliver, D. Raba and J. Freixenet Breast Skin-Line Segmentation Using Contour Growing. 3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA'07). LNCS 4478 pp.564-571. Girona. 2007

  85. [IbPRIA07c] A. Oliver, X. Lladó, J. Martí, R. Martí, J. Freixenet False Positive Reduction in Breast Mass Detection using Two-Dimensional PCA. 3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA'07). LNCS 4478 pp. 154-161. Girona. 2007

  86. [IbPRIA07d] D. Raba, M. Peracaula, R. Martí J. Martí On the Detection of Regions-of-Interest in Dynamic Contrast-Enhanced MRI. 3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA'07). LNCS 4477 pp. 129-136. Girona. 2007

  87. [QCAV07] R. Martí, J. Martí, J. Freixenet, J.C. Vilanova, J. Barceló Robust Speckle Detection in Ultrasound Images. Evaluation Aspects. 8th International Conference on Quality Control by Artificial Vision (QCAV'07), Le Creusot, France, 2007. Proceedings of SPIE Vol. 6356.

  88. [MICCAI06] A.Oliver, J.Freixenet, R.Martí, and R.Zwiggelaar. A comparison of breast tissue classification techniques. International Conference on Medical Image Computing and Computer Assisted Intervention, LCNS 4191, pp 872-879 2006. Copenhagen, Denmark, 2006.

  89. [ICPR06a] A.Oliver, J.Freixenet, R.Martí, A.Bosch, and J.Martí A new approach to the classification of mammographic masses and normal breast tissue. International Conference on Pattern Recognition vol 4 pp 707-710. Hong Kong. August 2006.

  90. [ICPR06b] A.Bosch, X.Muñoz, A.Oliver, and R.Martí. Object and scene classification: what does a supervised approach provide us? International Conference on Pattern Recognition (ICPR 2006). Vol 1, pp 773-777. Hong Kong.August 2006.

  91. [IWDM06] R. Martí, D. Raba, A. Oliver and R. Zwiggelaar Mammographic Registration: Proposal and Evaluation of a new approach Lecture Notes in Computer Science 4046, pp. 213-220. International Workshop on Digital Mammography, Manchester, 2006.

  92. [CARS05] D.Raba, J. Martí, R. Martí and M. Peracaula Breast mammography asymmetry estimation based on fractal and texture analysis Computed Aided Radiology and Surgery (CARS 2005). Elsevier, International Congress Series, 1281.

  93. [IWDM04] Marti J, Freixenet J, Peracaula M, Oliver A, Raba D, Espunya J, Pont J, Marti R Automatic segmentation of microcalcifications based on the fusion of different algorithms over CC and MLO views. 7th International Workshop on Digital Mammography, Durham, North Carolina, USA, 2004

  94. [IWDM02a] R. Marti, C. Rubin, E. Denton and R. Zwiggelaar Mammographic X-ray and MR correspondence 6th International Workshop on Digital Mammography. Proceedings of the IWDM 2002, pp. 536-538. Springer. Bremen (Germany) 2002

  95. [IWDM02b] R. Marti, C. Rubin, E. Denton and R. Zwiggelaar Tracking of 3D structures in MR mammography 6th International Workshop on Digital Mammography. Proceedings of the IWDM 2002, pp. 527-529. Springer. Bremen (Germany) 2002

  96. [IWDM02c] R. Zwiggelaar, P. Planiol, J. Martí, R. Marti, L. Blot, E. Denton and C. Rubin EM Texture Segmentation of Mammographic Images 6th International Workshop on Digital Mammography. Proceedings of the IWDM 2002, pp. 223-227. Springer. Bremen (Germany) 2002

  97. [BMVC01] R. Marti, R. Zwiggelaar and C. Rubin Tracking mammographic structures over time 12th British Machine Vision Conference. Proceedings of the 12th British Machine Vision Conference, pp. 143-152, 2001 Manchester (UK), 2001

  98. [IPMI01] R. Marti, R. Zwiggelaar and C. Rubin Automatic registration of mammograms based on linear structures Information Processing in Medical Imaging (IPMI 01). Lecture Notes on Computer Science, pp. 162-188, 2001. U.C. Davis (EUA), 2001

  99. [ICPR00] R. Marti, R. Zwiggelaar and C. Rubin A Novel Similarity Measure to Evaluate Image Correspondence International Conference on Pattern Recognition. IEEE Computer Society, pp. 171-174, 2000, Barcelona (Spain).

  100. [IWDM00a] R. Zwiggelaar and R. Marti Detecting linear structures in mammographic images 5th International Workshop on Digital Mammography Proceedings of the 5th IWDM. Medical Physics Publishing, 2000 Toronto (Canada).

  101. [IWDM00b] R. Marti, R. Zwiggelaar and C. Rubin. Comparing image correspondence in mammograms 5th International Workshop on Digital Mammography Proceedings of the 5th IWDM. Medical Physics Publishing, pp. 295-301, 2000 Toronto (Canadá).

National Conferences


  1. [InnoEducaTIC19] X. Cufi, J. Freixenet, E. Muntaner, A. Figueras, R. Martí and A. Renart Talleres de robótica submarina para atraer a estudiantes jóvenes hacia la ciencia y la ingeniería: Construir y pilotar un ROV. Dos ediciones especiales en la India. VI Jornadas Iberoamericanas de Innovación Educativa en el Ámbito de las TIC y las TAC. November 2019, Las Palmas de Gran Canaria, Spain.

  2. [SERAM18a] R. Martí, J.C. Vilanova, E. Pérez, M. Sentís, O.Diaz. SMARTER: análisis de imágenes para la mejora del diagnóstico del cáncer de mama. Congreso Nacional Sociedad Española de Radiología Médica (SERAM). May 2018, Pamplona, Spain.

  3. [SERAM18b] R. Agarwal, O. Diaz, X. Lladó, A. Gubern Mérida, J.C. Vilanova, R. Martí Segmentación semiautomática en ecografía mamaria automatizada (ABUS). Congreso Nacional Sociedad Española de Radiología Médica (SERAM). May 2018, Pamplona, Spain.

  4. [SERAM18c] O. Diaz, A. Gubern-Merida, S. Diekmann, R. Mann, R. Martí. Clasificación automática del realce parenquimatoso de fondo (BPE) en DCE-MRI. Congreso Nacional Sociedad Española de Radiología Médica (SERAM). May 2018, Pamplona, Spain.

  5. [CASEIB 2010] C.Mata, X.Lladó, R.Martí, J.Freixenet, A.Oliver, and J.Martí Aplicación web para la gestión de una base de datos pública en mamografía digital: MamoDB. Congreso Anual de la Sociedad Española de Ingeniería Biomédica, pp 175-178. Madrid, Spain. November 2010.

  6. [EICC08] J. Salvi, R. Martí, X. Cufí.Master Europeu en Visió i Robòtica Reconegut pel Programa Erasmus Mundus de la Unió Europea III Congrés d'Enginyeria i Cultura Catalana. Associació d'Enginyeria i Cultura Catalana, EiCC'08, Palma de Mallorca (Spain) December 4-6, 2008.

  7. [MIUA07] A.Oliver, X.Lladó, R.Martí, J.Freixenet, and R.Zwiggelaar Classifying mammograms using texture information Medical Image Understanding and Analysis, pp 223-227. Aberystwyth, Wales, UK. July 2007.

  8. [MIUA06] A.Oliver, J.Freixenet, R.Martí, E.R.E.Denton and R.Zwiggelaar. Mammographic mass eigendetection. Medical Image Understanding and Analysis, pp 71-75, Manchester, UK. July 2006

  9. [CCIA05] R. Martí, D. Raba, C. Rubin and Reyer Zwiggelaar Detecting Mammographic Abnormalities from Image Registration Results Congrés Català d'intel.ligència Artificial (CCIA 05) Artificial Intelligence Research and Development. Frontiers in Artificial Intelligence and Applications, pp.59-66. Alghero, Italia, 2005

  10. [ACMG04] Pont J., Martí J., Bassaganyas R., Raba D., Martí R., Oliver A., Peracaula M., Espunya J., Golabardes E., Freixenet J. Cerca de documentació complementària en bases de dades de mamografies digitals per ajudar en el diagnòstic precoç. Agrupación de Ciencias médicas de Gerona. XX Jornada de Clausura (curso 2003-2004), Roses, Girona, 2004

  11. [CCSPM04] Pont J., Martí J., Bassaganyas R., Raba D., Martí R., Oliver A., Peracaula M., Espunya J., Golabardes E., Freixenet J. Cerca de documentació complementària en bases de dades de mamografies digitals per ajudar en el diagnòstic precoç. III Congrés Català de Sinologia i Patologia Mamària, Girona, 2004

  12. [MIUA02] R. Marti, R. Zwiggelaar, C. Rubin and E. Denton 2D-3D Correspondence in Mammography, Medical Image Understanding and Analysis. Proceedings of the 6th Medical Image Understanding and Analysis, pp. 101-104, 2002. Portsmouth (UK) 2002.

  13. [MIUA01] R. Marti, R. Zwiggelaar and C. Rubin Automatic mammographic registration: towards the detection of abnormalities Proceedings of 5th Medical Image Understanding and Analysis Conference, pp. 149-152, 2001 Birmingham (UK).

  14. [SNRFAI01] R. Marti, R. Zwiggelaar and C. Rubin Automatic point correspondence and registration based on linear structures Proceedings of 9th Spanish Symposium on Pattern Recognition and Image Processing, pp. 19-24, 2001 Benicássim (Spain).

  15. [MIUA00] R. Zwiggelaar, R. Marti and C.R.M. Boggis Detection of linear structures in mammographic images Medical Image Understanding and Analysis, Procedings of 4th Medical Image Understanding and Analysis Conference London (UK), 2000.


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