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Fully convolutional network and sparsity-based dictionary learning for liver lesion detection in CT examinations.

, , , , , and . Neurocomputing, (2018)

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Learning Texture Discrimination Rules in a Multiresolution System., , , and . IEEE Trans. Pattern Anal. Mach. Intell., 16 (9): 894-901 (1994)Automatic detection of specular reflections in uterine cervix images., and . Medical Imaging: Image Processing, volume 6144 of SPIE Proceedings, page 61446E. SPIE, (2006)White matter tractographies registration using Gaussian mixture modeling., , and . Medical Imaging: Image Processing, volume 6914 of SPIE Proceedings, page 69142G. SPIE, (2008)Automatic identification of bacterial types using statistical imaging methods., , , and . Medical Imaging: Image Processing, volume 5032 of SPIE Proceedings, SPIE, (2003)Image patch-based method for automated classification and detection of focal liver lesions on CT., , , and . Medical Imaging: Computer-Aided Diagnosis, volume 8670 of SPIE Proceedings, page 86700Y. SPIE, (2013)Pneumothorax detection in chest radiographs using local and global texture signatures., , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 9414 of SPIE Proceedings, page 94141P. SPIE, (2015)Supervised Domain Adaptation by transferring both the parameter set and its gradient., , and . Neurocomputing, (December 2023)Joint Liver Lesion Segmentation and Classification via Transfer Learning., and . CoRR, (2020)Deep Feature Learning from a Hospital-Scale Chest X-ray Dataset with Application to TB Detection on a Small-Scale Dataset., and . EMBC, page 4076-4079. IEEE, (2019)A review of deep learning in medical imaging: Image traits, technology trends, case studies with progress highlights, and future promises., , , , , , , , and . CoRR, (2020)