Huazhu Fu; Mona K. Garvin; Tom MacGillivray; Yanwu Ophthalmic Medical Image Analysis 9783030329556

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Автор: Huazhu Fu; Mona K. Garvin; Tom MacGillivray; Yanwu
Название: Ophthalmic Medical Image Analysis
ISBN: 9783030329556
Издательство: Springer
Классификация:

Аппаратное обеспечение коипьютеров

Математика для специалистов в области теории вычислительных систем

Искусственный интеллект

Машинное зрение

ISBN-10: 3030329550
Обложка/Формат: Soft cover
Страницы: 192
Вес: 0.32 кг.
Дата издания: 2019
Серия: Image Processing, Computer Vision, Pattern Recognition, and Graphics
Язык: English
Издание: 1st ed. 2019
Иллюстрации: 78 illustrations, color; 2 illustrations, black and white; xi, 192 p. 80 illus., 78 illus. in color.
Размер: 234 x 156 x 11
Читательская аудитория: Professional & vocational
Основная тема: Computer Science
Подзаголовок: 6th International Workshop, OMIA 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, Proceedings
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание:

Dictionary Learning Informed Deep Neural Network with Application to OCT Images.- Structure-aware Noise Reduction Generative Adversarial Network for Optical Coherence Tomography Image.- Region-Based Segmentation of Capillary Density in Optical Coherence Tomography Angiography.- An ampliﬁed-target loss approach for photoreceptor layer segmentation in pathological OCT scans.- Foveal avascular zone segmentation in clinical routine ﬂuorescein angiographies using multitask learning.- Guided M-Net for High-resolution Biomedical Image Segmentation with Weak Boundaries.- 3D-CNN for Glaucoma Detection using Optical Coherence Tomography.- Semi-supervised Adversarial Learning for Diabetic Retinopathy Screening.- Shape Decomposition of Foveal Pit Morphology using Scan Geometry Corrected OCT.- U-Net with spatial pyramid pooling for drusen segmentation in optical coherence tomography.- Deriving Visual Cues from Deep Learning to Achieve Subpixel Cell Segmentation in Adaptive Optics Retinal Images.- Robust Optic Disc Localization by Large Scale Learning.- The Channel Attention based Context Encoder Network for Inner Limiting Membrane Detections.- Fundus Image based Retinal Vessel Segmentation Utilizing A Fast and Accurate Fully Convolutional Network.- Network pruning for OCT image classiﬁcation.- An improved MPB-CNN segmentation method for edema area and neurosensory retinal detachment in SD-OCT images.- Encoder-Decoder Attention Network for Lesion Segmentation of Diabetic Retinopathy.- Multi-Discriminator Generative Adversarial Networks for improved thin retinal vessel segmentation.- Fovea Localization in Fundus Photographs by Faster R-CNN with Physiological Prior.- Aggressive Posterior Retinopathy of Prematurity Automated Diagnosis via a Deep Convolutional Network.- Automated Stage Analysis of Retinopathy of Prematurity Using Joint Segmentation and Multi-Instance Learning.- Retinopathy Diagnosis using Semi-supervised Multi-channel Generative Adversarial Network.

Дополнительное описание: Dictionary Learning Informed Deep Neural Network with Application to OCT Images.- Structure-aware Noise Reduction Generative Adversarial Network for Optical Coherence Tomography Image.- Region-Based Segmentation of Capillary Density in Optical Coherence T

Ophthalmic Medical Image Analysis, Huazhu Fu; Mona K. Garvin; Tom MacGillivray; Yanwu