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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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Cross-modality synthesis from CT to PET using FCN and GAN networks for improved automated lesion detection., , , , , , , and . Eng. Appl. Artif. Intell., (2019)Virtual PET Images from CT Data Using Deep Convolutional Networks: Initial Results., , , , and . SASHIMI@MICCAI, volume 10557 of Lecture Notes in Computer Science, page 49-57. Springer, (2017)Fully Convolutional Network for Liver Segmentation and Lesions Detection., , , , and . LABELS/DLMIA@MICCAI, volume 10008 of Lecture Notes in Computer Science, page 77-85. (2016)Fully convolutional network and sparsity-based dictionary learning for liver lesion detection in CT examinations., , , , , and . Neurocomputing, (2018)Weakly Supervised Attention Model for RV StrainClassification from volumetric CTPA Scans., , , , , , and . CoRR, (2021)Fully automatic detection of renal cysts in abdominal CT scans., , , , , and . Int. J. Comput. Assist. Radiol. Surg., 13 (7): 957-966 (2018)Automatic detection and segmentation of liver metastatic lesions on serial CT examinations., , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 9035 of SPIE Proceedings, page 903519. SPIE, (2014)A Simple Free-Text-like Method for Extracting Semi-Structured Data from Electronic Health Records: Exemplified in Prediction of In-Hospital Mortality., , , , , , , , and . Big Data Cogn. Comput., 5 (3): 40 (2021)The Liver Tumor Segmentation Benchmark (LiTS)., , , , , , , , , and 49 other author(s). CoRR, (2019)Improved Patch-Based Automated Liver Lesion Classification by Separate Analysis of the Interior and Boundary Regions., , , , , , , and . IEEE J. Biomed. Health Informatics, 20 (6): 1585-1594 (2016)