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Myopic Maculopathy Analysis : MICCAI Challenge MMAC 2023, Held in Conjunction with MICCAI 2023, Virtual Event, October 8–12, 2023, Proceedings / edited by Bin Sheng, Hao Chen, Tien Yin Wong.

Springer Nature - Springer Computer Science eBooks 2024 English International Available online

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Format:
Book
Contributor:
Sheng, Bin, editor.
Chen, Hao, editor.
Wong, Tien Yin, editor.
Series:
Lecture Notes in Computer Science, 1611-3349 ; 14563
Language:
English
Subjects (All):
Artificial intelligence.
Computer vision.
Artificial Intelligence.
Computer Vision.
Local Subjects:
Artificial Intelligence.
Computer Vision.
Physical Description:
1 online resource (131 pages)
Edition:
1st ed. 2024.
Place of Publication:
Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Summary:
This book constitutes the MICCAI Challenge, MMAC 2023, that held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, which took place in October 2023. The 11 long papers included in this volume presents a wide range of state-of-the-art deep learning methods developed for the various tasks presented in the challenge.
Contents:
Automated Detection of Myopic Maculopathy in MMAC 2023: Achievements in Classification, Segmentation, and Spherical Equivalent Prediction
Swin-MMC: Swin-Based Model for Myopic Maculopathy Classification in Fundus Images
Towards Label-efficient Deep Learning for Myopic Maculopathy Classification
Ensemble Deep Learning Approaches for Myopic Maculopathy Plus Lesions Segmentation
Beyond MobileNet: An improved MobileNet for Retinal Diseases
Prediction of Spherical Equivalent With Vanilla ResNet
Semi-supervised learning for Myopic Maculopathy Analysis
A Clinically Guided Approach for Training Deep Neural Networks for Myopic Maculopathy Classification
Classification of Myopic Maculopathy Images with Self-supervised Driven Multiple Instance Learning Network
Self-supervised Learning and Data Diversity based Prediction of Spherical Equivalent
Myopic Maculopathy Analysis using Multi-Task Learning and Pseudo Labeling.
Notes:
Includes bibliographical references and index.
ISBN:
3-031-54857-4

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