Medical Image Understanding and Analysis

28th Annual Conference, MIUA 2024, Manchester, UK, July 24¿26, 2024, Proceedings, Part II
Herausgegeben:Yap, Moi Hoon; Kendrick, Connah; Behera, Ardhendu; Cootes, Timothy; Zwiggelaar, Reyer

• Broschiertes Buch

Produktbeschreibung

This two-volume set LNCS 14859-14860 constitutes the proceedings of the 28th Annual Conference on Medical Image Understanding and Analysis, MIUA 2024, held in Manchester, UK, during July 24-26, 2024.

The 59 full papers included in this book were carefully reviewed and selected from 93 submissions. They were organized in topical sections as follows:

Part I : Advancement in Brain Imaging; Medical Images and Computational Models; and Digital Pathology, Histology and Microscopic Imaging.

Part II : Dental and Bone Imaging; Enhancing Low-Quality Medical Images; Domain Adaptation and Generalisation; and Dermatology, Cardiac Imaging and Other Medical Imaging.

Produktdetails

• Lecture Notes in Computer Science 14860
• Verlag: Springer / Springer Nature Switzerland / Springer, Berlin
• Artikelnr. des Verlages: 978-3-031-66957-6
• 2024
• Seitenzahl: 480
• Erscheinungstermin: 24. Juli 2024
• Englisch
• Abmessung: 235mm x 155mm x 26mm
• Gewicht: 721g
• ISBN-13: 9783031669576
• ISBN-10: 3031669576
• Artikelnr.: 70986895

Inhaltsangabe

.- Dental and Bone Imaging.

.- Enhancing Cephalometric Landmark Detection with a Two-Stage Cascaded CNN on Multi-Resolution Multi-Modal Data.

.- Enhancing Dental Diagnostics: Advanced Image Segmentation Models for Teeth Identification and Enumeration.

.- 3D Bone Shape from CT-Scans Provides an Objective Measure of Osteoarthritis Severity: data from the IMI-APPROACH study.

.- CNN-based osteoporotic vertebral fracture prediction and risk assessment on MrOS CT data: Impact of CNN model architecture.

.- Analysis of leg bones from whole body DXA in the UK Biobank.

.- H-FCBFormer: Hierarchical Fully Convolutional Branch Transformer for Occlusal Contact Segmentation with Articulating Paper.

.- Enhancing Low-Quality Medical Images.

.- Ultrasound Confidence Maps with Neural Implicit Representation.

.- Blurry Boundary Segmentation with Semantic-guided Feature Learning.

.- SA-GCN: Scale Adaptive Graph Convolutional Network for ASD Identification.

.- Resolution-Invariant Medical Image Segmentation using Fourier Neural Operators.

.- YOLO-TL:A Tiny Object Segmentation Framework for Low Quality Medical Images.

.- Superresolution of real-world multiscale bone CT verified with clinical bone measures.

.- Reconstructing MRI parameters using a noncentral chi noise model.

.- Domain Adaptation and Generalisation.

.- AdaptiveSAM: Towards Efficient Tuning of SAM for Surgical Scene Segmentation.

.- Analysing Variables for 90-Day Functional-Outcome Prediction of Endovascular Thrombectomy.

.- Multimodal Deformable Image Registration for Long-COVID Analysis Based on Progressive Alignment and Multi-perspective Loss.

.- Confounder-Aware Image Synthesis for Pathology Segmentation in New Magnetic Resonance Imaging Sequences.

.- Prediction of total metabolic tumor volume from tissue-wise FDG-PET/CT projections, interpreted using cohort saliency analysis.

.- Expert model prediction through feature matching.

.- Enhancing Cross-Institute Generalisation of GNNs in Histopathology through Multiple Embedding Graph Augmentation (MEGA).

.- PMT: Partial-Modality Translation Based on Diffusion Models for Prostate Magnetic Resonance and Ultrasound Image Registration.

.- Fine-grained Medical Image Synthesis with Dual-Attention Adversarial Learning.

.- Dermatology, Cardiac Imaging and Other Medical Imaging.

.- Enhancing Skin Lesion Classification: A Self-Attention Fusion Approach with Vision Transformer.

.- Optimizing Melanoma Prognosis through Synergistic Preprocessing and Deep Learning Architecture for Dermoscopic Thickness Prediction.

.- The Effect of Image Preprocessing Algorithms on Diabetic Foot Ulcer Classification.

.- Synthetic Balancing of Cardiac MRI Datasets.

.- EchoVisuAL: Efficient Segmentation of Echocardiograms using Deep Active Learning.

.- Improving Automated Ultrasound Infant Hip Screening using an Integrated Clinical Classification Loss.

.- Deep learning models to automate the scoring of hand radiographs for Rheumatoid Arthritis.

.- Radiomic Analysis for Prediction of Preterm Birth.

.- Hierarchical multi-label learning for musculoskeletal phenotyping in mice.

.- MIUA 2023 Overlooked Paper.

.- Prediction of Incident Atrial Fibrillation in Population with Ischemic Heart Disease using Machine Learning with Radiomics and ECG Markers.