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Medical image understanding and analysis = 28th Annual Conference, MIUA 2024, Manchester, UK, July 24-26, 2024 : proceedings.. Part II /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Medical image understanding and analysis/ edited by Moi Hoon Yap ... [et al.].
Reminder of title:	28th Annual Conference, MIUA 2024, Manchester, UK, July 24-26, 2024 : proceedings.
remainder title:	MIUA 2024
other author:	Yap, Moi Hoon.
corporate name:	Workshop on the Preservation of Stability under Discretization
Published:	Cham :Springer Nature Switzerland : : 2024.,
Description:	xx, 458 p. :ill. (chiefly col.), digital ; : 24 cm.;
Contained By:	Springer Nature eBook
Subject:	Diagnostic imaging - Handbooks, manuals, etc. -
Online resource:	https://doi.org/10.1007/978-3-031-66958-3
ISBN:	9783031669583

Medical image understanding and analysis = 28th Annual Conference, MIUA 2024, Manchester, UK, July 24-26, 2024 : proceedings.. Part II /
Medical image understanding and analysis28th Annual Conference, MIUA 2024, Manchester, UK, July 24-26, 2024 : proceedings.Part II /[electronic resource] :MIUA 2024edited by Moi Hoon Yap ... [et al.]. - Cham :Springer Nature Switzerland :2024. - xx, 458 p. :ill. (chiefly col.), digital ;24 cm. - Lecture notes in computer science,148601611-3349 ;. - Lecture notes in computer science ;6140..

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.

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.

ISBN: 9783031669583

Standard No.: 10.1007/978-3-031-66958-3doiSubjects--Topical Terms:

745141
Diagnostic imaging
--Handbooks, manuals, etc.

LC Class. No.: RC78.7.D53

Dewey Class. No.: 616.0754

Medical image understanding and analysis = 28th Annual Conference, MIUA 2024, Manchester, UK, July 24-26, 2024 : proceedings.. Part II /
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