Myopic Maculopathy Analysis -

Myopic Maculopathy Analysis

MICCAI Challenge MMAC 2023, Held in Conjunction with MICCAI 2023, Virtual Event, October 8–12, 2023, Proceedings

Bin Sheng, Hao Chen, Tien Yin Wong (Herausgeber)

Buch | Softcover
X, 121 Seiten
2024 | 2024
Springer International Publishing (Verlag)
978-3-031-54856-7 (ISBN)
53,49 inkl. MwSt

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.


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.

Erscheinungsdatum
Reihe/Serie Lecture Notes in Computer Science
Zusatzinfo X, 121 p. 33 illus., 31 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Themenwelt Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Schlagworte Artificial Intelligence • computer vision • Deep learning • Knowledge Representation and Reasoning • machine learning • Medical Images • Neural networks • Scene Understanding
ISBN-10 3-031-54856-6 / 3031548566
ISBN-13 978-3-031-54856-7 / 9783031548567
Zustand Neuware
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