Search results for ""Author M. Emre Celebi""

Dermoscopy is a noninvasive skin imaging technique that uses optical magnification and either liquid immersion or cross-polarized lighting to make subsurface structures more easily visible when compared to conventional clinical images. It allows for the identification of dozens of morphological features that are particularly important in identifying malignant melanoma. Dermoscopy Image Analysis summarizes the state of the art of the computerized analysis of dermoscopy images. The book begins by discussing the influence of color normalization on classification accuracy and then: Investigates gray-world, max-RGB, and shades-of-gray color constancy algorithms, showing significant gains in sensitivity and specificity on a heterogeneous set of images Proposes a new color space that highlights the distribution of underlying melanin and hemoglobin color pigments, leading to more accurate classification and border detection results Determines that the latest border detection algorithms can achieve a level of agreement that is only slightly lower than the level of agreement among experienced dermatologists Provides a comprehensive review of various methods for border detection, pigment network extraction, global pattern extraction, streak detection, and perceptually significant color detection Details a computer-aided diagnosis (CAD) system for melanomas that features an inexpensive acquisition tool, clinically meaningful features, and interpretable classification feedback Presents a highly scalable CAD system implemented in the MapReduce framework, a novel CAD system for melanomas, and an overview of dermatological image databases Describes projects that made use of a publicly available database of dermoscopy images, which contains 200 high-quality images along with their medical annotations Dermoscopy Image Analysis not only showcases recent advances but also explores future directions for this exciting subfield of medical image analysis, covering dermoscopy image analysis from preprocessing to classification.

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This double volume set LNCS 14393-14394 constitutes the proceedings from the workshops held at the 26th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2023 Workshops, which took place in Vancouver, BC, Canada, in October 2023. The 54 full papers together with 14 short papers presented in this volume were carefully reviewed and selected from 123 submissions from all workshops. The papers of the workshops are presenting the topical sections: Eighth International Skin Imaging Collaboration Workshop (ISIC 2023) First Clinically-Oriented and Responsible AI for Medical Data Analysis (Care-AI 2023) Workshop First International Workshop on Foundation Models for Medical Artificial General Intelligence (MedAGI 2023) Fourth Workshop on Distributed, Collaborative and Federated Learning (DeCaF 2023) First MICCAI Workshop on Time-Series Data Analytics and Learning First MICCAI Workshop on Lesion Evaluation and Assessment with Follow-Up (LEAF) AI For Treatment Response Assessment and predicTion Workshop (AI4Treat 2023) Fourth International Workshop on Multiscale Multimodal Medical Imaging (MMMI 2023) Second International Workshop on Resource-Effcient Medical Multimodal Medical Imaging Image Analysis (REMIA 2023)

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