Medical Image Understanding and Analysis : 27th Annual Conference, MIUA 2023, Aberdeen, UK, July 19–21, 2023, Proceedings / edited by Gordon Waiter, Tryphon Lambrou, Georgios Leontidis, Nir Oren, Teresa Morris, Sharon Gordon.

Format:

Book

Contributor:

Waiter, Gordon, editor.

Series:

Lecture Notes in Computer Science, 1611-3349 ; 14122

Language:

English

Subjects (All):

Image processing--Digital techniques.

Image processing.

Computer vision.

Application software.

Artificial intelligence.

Machine learning.

Signal processing.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Computer and Information Systems Applications.

Artificial Intelligence.

Machine Learning.

Signal, Speech and Image Processing.

Local Subjects:

Computer Imaging, Vision, Pattern Recognition and Graphics.

Computer and Information Systems Applications.

Artificial Intelligence.

Machine Learning.

Signal, Speech and Image Processing.

Physical Description:

1 online resource (346 pages)

Edition:

1st ed. 2024.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2024.

Summary:

This book constitutes the proceedings of the 27th Annual Conference on Medical Image Understanding and Analysis, MIUA 2023, which took place in Aberdeen, UK, during July 19–21, 2023. The 24 full papers presented in this book were carefully reviewed and selected from 42 submissions. They were organized in topical sections as follows: Image interpretation; radiomics, predictive models and quantitative imaging; image classification; and biomarker detection.

Contents:

Segmentation of White Matter Hyperintensities and Ischaemic Stroke Lesions in Structural MRI

A Deep Learning Based Approach to Semantic Segmentation of Lung Tumour Areas in Gross Pathology Images

Iterative Refinement Algorithm for Liver Segmentation Ground-Truth Generation using Fine-Tuning Weak Labels for CT and Structural MRI

M-VAAL: Multimodal Variational Adversarial Active Learning for Downstream Medical Image Analysis Tasks

BliMSR: Blind degradation modelling for generating high-resolution medical images

Efficient Semantic Segmentation of Nuclei in Histopathology Images Using Segformer

Cross-Modality Deep Transfer Learning: Application to Liver Segmentation in CT and MRI

Can SegFormer be a True Competitor to U-Net for Medical Image Segmentation

Harnessing the Potential of Deep Learning for Total Shoulder Implant Classification: A Comparative Study

Deep Facial Phenotyping with Mixup Augmentation

Context Matters:Cross-domain Cell Detection in Histopathology Images via Contextual Regularization

TON-ViT: A Neuro-Symbolic AI based on Task Oriented Network with a Vision Transformer

A new similarity metric for deformable registration of MALDI-MS and MRI images

Decoding Individual and Shared Experiences of Media Perception using CNN architectures

Revolutionizing Cancer Diagnosis through Hybrid Self-supervised Deep Learning: EfficientNet with Denoising Autoencoder for Semantic Segmentation of Histopathological Images

Baseline Models for Action Recognition of Unscripted Casualty Care Dataset

Web-based AI System for Medical Image Segmentation

A new approach for identifying skin diseases from dermatological RGB images using source separation

Pseudo-SPR map Generation from MRI using U-Net Architecture for Ion Beam Therapy Application

Generalised 3D Medical Image Registration with Learned Shape Encodings

Retinal Image Screening with Topological Machine Learning

Neural Network Pruning for Real-time Polyp Segmentation

A Novel Approach to Breast Cancer Segmentation using U-Net Model with Attention Mechanisms and FedProx Algorithm

Super Images - A New 2D Perspective on 3D Medical Imaging Analysis.

Notes:

Includes bibliographical references and index.

Other Format:

Print version: Waiter, Gordon Medical Image Understanding and Analysis

ISBN:

3-031-48593-9