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Comparing endoscopic imaging configurations in computer-aided celiac disease diagnosis.

, , , and . IPTA, page 446-451. IEEE, (2015)

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Convolutional Neural Network Architectures for the Automated Diagnosis of Celiac Disease., , , and . CARE@MICCAI, volume 10170 of Lecture Notes in Computer Science, page 104-113. Springer, (2016)Feature Extraction with Intrinsic Distortion Correction in Celiac Disease Imagery: No Need for Rasterization., , and . MCV, volume 8331 of Lecture Notes in Computer Science, page 196-204. Springer, (2013)Is a Precise Distortion Estimation Needed for Computer Aided Celiac Disease Diagnosis?, , and . ICISP, volume 8509 of Lecture Notes in Computer Science, page 620-628. Springer, (2014)Degradation Adaptive Texture Classification: A Case Study in Celiac Disease Diagnosis Brings New Insight., , and . ICIAR (2), volume 8815 of Lecture Notes in Computer Science, page 263-273. Springer, (2014)Fully-Automated CNN-Based Computer Aided Celiac Disease Diagnosis., , , , , and . ICIAP (2), volume 10485 of Lecture Notes in Computer Science, page 467-478. Springer, (2017)Quality Based Information Fusion in Fully Automatized Celiac Disease Diagnosis., , and . GCPR, volume 8753 of Lecture Notes in Computer Science, page 666-677. Springer, (2014)Automated Marsh-like classification of celiac disease in children using local texture operators., , , , and . Comput. Biol. Medicine, 41 (6): 313-325 (2011)Incorporating human knowledge in automated celiac disease diagnosis., , , , , and . IPTA, page 1-6. IEEE, (2016)Feature extraction from multi-directional multi-resolution image transformations for the classification of zoom-endoscopy images., , , , , and . Pattern Anal. Appl., 12 (4): 407-413 (2009)Endoscope Distortion Correction Does Not (Easily) Improve Mucosa-Based Classification of Celiac Disease., , , and . MICCAI (3), volume 7512 of Lecture Notes in Computer Science, page 574-581. Springer, (2012)