
Information Processing in Medical Imaging
28th International Conference, IPMI 2023, San Carlos de Bariloche, Argentina, June 18-23, 2023, Proceedings
Springer (Publisher)
Published on 8. June 2023
Book
Paperback/Softback
XXI, 839 pages
978-3-031-34047-5 (ISBN)
Description
This book constitutes the proceedings of the 28th International Conference on Information Processing in Medical Imaging, IPMI 2023, which took place in San Carlos de Bariloche, Argentina, in June 2023.
The 63 full papers presented in this volume were carefully reviewed and selected from 169 submissions. They were organized in topical sections as follows: biomarkers; brain connectomics; computer-aided diagnosis/surgery; domain adaptation; geometric deep learning; groupwise atlasing; harmonization; federated learning; image synthesis; image enhancement; multimodal learning; registration; segmentation; self supervised learning; surface analysis and segmentation.
More details
Series
Edition
1st ed. 2023
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
16 s/w Abbildungen, 240 farbige Abbildungen
XXI, 839 p. 256 illus., 240 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 46 mm
Weight
1282 gr
ISBN-13
978-3-031-34047-5 (9783031340475)
DOI
10.1007/978-3-031-34048-2
Schweitzer Classification
Other editions
Additional editions

Alejandro Frangi | Marleen de Bruijne | Demian Wassermann
Information Processing in Medical Imaging
28th International Conference, IPMI 2023, San Carlos de Bariloche, Argentina, June 18-23, 2023, Proceedings
E-Book
06/2023
Springer
€106.99
Available for download
Content
Biomarkers Resolving quantitative MRI model degeneracy with machine learning via training data distribution design.- Subtype and stage inference with timescales.- Brain connectomics HoloBrain: A Harmonic Holography for Self-organized Brain Function.- Species-Shared and -Specific Brain Functional Connectomes Revealed by Shared-Unique Variational Autoencoder.- mSPD-NN: A Geometrically Aware Neural Framework for Biomarker Discovery from Functional Connectomics Manifolds.- Computer-Aided Diagnosis/Surgery Diffusion Model based Semi-supervised Learning on Brain Hemorrhage Images for Efficient Midline Shift Quantification.- Don't PANIC: Prototypical Additive Neural Network for Interpretable Classification of Alzheimer's Disease.- Filtered trajectory recovery: a continuous extension to event-based model for Alzheimer's disease progression modeling.- Live image-based neurosurgical guidance and roadmap generation using unsupervised embedding.- Meta-information-aware Dual-path Transformer for Differential Diagnosis of Multi-type Pancreatic Lesions in Multi-phase CT.- MetaViT: Metabolism-Aware Vision Transformer for Differential Diagnosis of Parkinsonism with 18F-FDG PET.- Multi-task Multi-instance Learning for Jointly Diagnosis and Prognosis of Early-stage Breast Invasive Carcinoma from Whole-slide Pathological Images.- On Fairness of Medical Image Classification with Multiple Sensitive Attributes via Learning Orthogonal Representations.- Pixel-level explanation of multiple instance learning models in biomedical single cell images.- Marr Transient Hemodynamics Prediction Using an Efficient Octree-Based Deep Learning Model.- Weakly Semi-Supervised Detection in Lung Ultrasound Videos.- Optimization Differentiable Gamma Index-based loss functions: accelerating Monte-Carlo radiotherapy dose simulation.- Diversified stochastic orthonormal projective non-negative matrix factorization for big neuroimaging data.- Reconstruction Deep Physics-informed Super-resolution of Cardiac 4D-flow MRI.- Fast-MC-PET: A Novel Deep Learning-aid Motion Correction and Reconstruction Framework for Accelerated PET.- MeshDeform: Surface Reconstruction of Subcortical Structures via Human Brain MRI.- Neural Implicit k-Space for Binning-free Non-Cartesian Cardiac MR Imaging.