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Deep Learning approach predicting breast tumor response to neoadjuvant treatment using DCE-MRI volumes acquired before and after chemotherapy., , , and . Medical Imaging: Computer-Aided Diagnosis, volume 10950 of SPIE Proceedings, page 109502I. SPIE, (2019)Cloud-based platform for computer vision applications., , , , and . ICSDE, page 195-200. ACM, (2017)Semi-automatic detection of cervical vertebrae in X-ray images using generalized hough transform., , and . IPTA, page 396-401. IEEE, (2012)A Texture Analysis Approach for Spine Metastasis Classification in T1 and T2 MRI., , , and . IWBBIO (2), volume 10814 of Lecture Notes in Computer Science, page 198-211. Springer, (2018)Content-based 3D shape retrieval using deep learning approach., , , and . LOPAL, page 56:1-56:4. ACM, (2018)MRI Breast Tumor Segmentation Using Different Encoder and Decoder CNN Architectures., , , and . Comput., 8 (3): 52 (2019)Vertebra identification using template matching modelmp and $K$ -means clustering., , and . Int. J. Comput. Assist. Radiol. Surg., 9 (2): 177-187 (2014)A Portable Multi-CPU/Multi-GPU Based Vertebra Localization in Sagittal MR Images., , , , and . ICIAR (2), volume 8815 of Lecture Notes in Computer Science, page 209-218. Springer, (2014)Automated Breast Tumor Segmentation in DCE-MRI Using Deep Learning., , , and . Cloudtech, page 1-6. IEEE, (2018)