Mitosis Domain Generalization and Diabetic Retinopathy Analysis : MICCAI Challenges MIDOG 2022 and DRAC 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18–22, 2022, Proceedings / edited by Bin Sheng, Marc Aubreville.

Format:

Book

Author/Creator:

Sheng, Bin.

Contributor:

Aubreville, Marc.

Series:

Lecture Notes in Computer Science, 1611-3349 ; 13597

Language:

English

Subjects (All):

Image processing--Digital techniques.

Image processing.

Computer vision.

Computers.

Application software.

Machine learning.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Computing Milieux.

Computer and Information Systems Applications.

Machine Learning.

Local Subjects:

Computer Imaging, Vision, Pattern Recognition and Graphics.

Computing Milieux.

Computer and Information Systems Applications.

Machine Learning.

Physical Description:

1 online resource (250 pages)

Edition:

1st ed. 2023.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2023.

Summary:

This book constitutes two challenges that were held in conjunction with the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which took place in Singapore during September 18-22, 2022. The peer-reviewed 20 long and 5 short papers included in this volume stem from the following three biomedical image analysis challenges: Mitosis Domain Generalization Challenge (MIDOG 2022), Diabetic Retinopathy Analysis Challenge (CRAC 2022) The challenges share the need for developing and fairly evaluating algorithms that increase accuracy, reproducibility and efficiency of automated image analysis in clinically relevant applications.

Contents:

Preface DRAC 2022

nnU-Net Pre- and Postprocessing Strategies for UW-OCTA Segmentation Tasks in Diabetic Retinopathy Analysis

Automated analysis of diabetic retinopathy using vessel segmentation maps as inductive bias

Bag of Tricks for Diabetic Retinopathy Grading of Ultra-wide Optical Coherence Tomography Angiography Images

Deep convolutional neural network for image quality assessment and diabetic retinopathy grading

Diabetic Retinal Overlap Lesion Segmentation Network

An Ensemble Method to Automatically Grade Diabetic Retinopathy with Optical Coherence Tomography Angiography Images

Bag of Tricks for Developing Diabetic Retinopathy Analysis Framework to Overcome Data Scarcity

Deep-OCTA: Ensemble Deep Learning Approaches for Diabetic Retinopathy Analysis on OCTA Images

Deep Learning-based Multi-tasking System for Diabetic Retinopathy in UW-OCTA images

Semi-Supervised Semantic Segmentation Methods for UW-OCTA Diabetic Retinopathy Grade Assessment

ImageQuality Assessment based on Multi-Model Ensemble Class-Imbalance Repair Algorithm for Diabetic Retinopathy UW-OCTA Images

An improved U-Net for diabetic retinopathy segmentation

A Vision transformer based deep learning architecture for automatic diagnosis of diabetic retinopathy in optical coherence tomography angiography

Segmentation, Classification, and Quality Assessment of UW-OCTA Images for the Diagnosis of Diabetic Retinopathy

Data Augmentation by Fourier Transformation for Class-Imbalance : Application to Medical Image Quality Assessment

Automatic image quality assessment and DR grading method based on convolutional neural network

A transfer learning based model ensemble method for image quality assessment and diabetic retinopathy grading

Automatic Diabetic Retinopathy Lesion Segmentation in UW-OCTA Images using Transfer Learning

Preface MIDOG 2022

Reference Algorithms for the Mitosis Domain Generalization (MIDOG) 2022 Challenge

Radial Prediction Domain Adaption Classifier for the MIDOG 2022 challenge

Detecting Mitoses with a Convolutional Neural Network for MIDOG 2022 Challenge

Tackling Mitosis Domain Generalization in Histopathology Images with Color Normalization

"A Deep Learning based Ensemble Model for Generalized Mitosis Detection in H&E stained Whole Slide Images"

Fine-Grained Hard-Negative Mining: Generalizing Mitosis Detection with a Fifth of the MIDOG 2022 Dataset

Multi-task RetinaNet for mitosis detection. .

Other Format:

Print version: Sheng, Bin Mitosis Domain Generalization and Diabetic Retinopathy Analysis

ISBN:

9783031336584

3031336585