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Deep Learning and Handcrafted Method Fusion: Higher Diagnostic Accuracy for Melanoma Dermoscopy Images.

, , , , , , , , , and . IEEE J. Biomed. Health Informatics, 23 (4): 1385-1391 (2019)

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Using Adaptive Thresholding and Skewness Correction to Detect Gray Areas in Melanoma In Situ Images., , , , , , and . IEEE Trans. Instrum. Meas., 61 (7): 1839-1847 (2012)An image feature-based approach to automatically find images for application to clinical decision support., , , , and . Comput. Medical Imaging Graph., 35 (5): 365-372 (2011)Fuzzy logic color detection: Blue areas in melanoma dermoscopy images., , , , , , , and . Comput. Medical Imaging Graph., 38 (5): 403-410 (2014)Increasing Melanoma Diagnostic Confidence: Forcing the Convolutional Network to Learn from the Lesion., , , , , and . CoRR, (2023)Feature based Sequential Classifier with Attention Mechanism., , , , , , , and . CoRR, (2020)Automatic Detection of Skin Cancer - Current Status, Path for the Future., , , , and . VISAPP (1), page 504-508. SciTePress, (2013)Medical Image Processing in the Age of Deep Learning - Is There Still Room for Conventional Medical Image Processing Techniques?., , and . VISIGRAPP (4: VISAPP), page 306-311. SciTePress, (2017)Graphical image classification combining an evolutionary algorithm and binary particle swarm optimization., , , , and . DRR, volume 8297 of SPIE Proceedings, page 829703. SPIE, (2012)Image Analysis Techniques for the Automated Evaluation of Subaxial Subluxation in Cervical Spine X-ray Images., , , , , and . CBMS, page 204-209. IEEE Computer Society, (2004)Deep learning-based dot and globule segmentation with pixel and blob-based metrics for evaluation., , , , , , , , , and 1 other author(s). Intell. Syst. Appl., (2022)