06653nam a22006135i 4500 978-3-031-66958-3 DE-He213 20251030112648.0 cr nn 008mamaa 240724s2024 sz | s |||| 0|eng d 9783031669583 978-3-031-66958-3 10.1007/978-3-031-66958-3 doi TA1634 UYQV bicssc COM016000 bisacsh UYQV thema Medical Image Understanding and Analysis [electronic resource] : 28th Annual Conference, MIUA 2024, Manchester, UK, July 24–26, 2024, Proceedings, Part II / edited by Moi Hoon Yap, Connah Kendrick, Ardhendu Behera, Timothy Cootes, Reyer Zwiggelaar. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. XX, 458 p. 172 illus., 153 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Lecture Notes in Computer Science, 1611-3349 ; 14860 -- 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. Computer vision. Artificial intelligence. 58441 Computers. 65793 Application software. Computer Vision. Artificial Intelligence. 58441 Computing Milieux. 66530 Computer and Information Systems Applications. Yap, Moi Hoon. editor. (orcid)0000-0001-7681-4287 https://orcid.org/0000-0001-7681-4287 edt http://id.loc.gov/vocabulary/relators/edt 81217 Kendrick, Connah. editor. (orcid)0000-0002-3623-6598 https://orcid.org/0000-0002-3623-6598 edt http://id.loc.gov/vocabulary/relators/edt 81218 Behera, Ardhendu. editor. edt http://id.loc.gov/vocabulary/relators/edt 81219 Cootes, Timothy. editor. edt http://id.loc.gov/vocabulary/relators/edt 81220 Zwiggelaar, Reyer. editor. edt http://id.loc.gov/vocabulary/relators/edt 81221 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031669576 Printed edition: 9783031669590 Lecture Notes in Computer Science, 1611-3349 ; 14860 https://doi.org/10.1007/978-3-031-66958-3 ZDB-2-SCS ZDB-2-SXCS ZDB-2-LNC 61885 61885