Del 15186 i serien Lecture Notes in Computer Science

Simplifying Medical Ultrasound

5th International Workshop, ASMUS 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings

Häftad, Engelska, 2024

AvAlberto Gomez,Bishesh Khanal,Andrew King,Ana Namburete

939 kr

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This book constitutes the proceedings of the 5th International Workshop on Simplifying Medical Ultrasound, ASMUS 2024, held in conjunction with MICCAI 2024, the 27th International Conference on Medical Image Computing and Computer-Assisted Intervention.

Produktinformation

Utgivningsdatum2024-10-05
Mått155 x 235 x 14 mm
Vikt388 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor233
FörlagSpringer International Publishing AG
ISBN9783031736469

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Medicinsk bildbehandling inom Medicin
Artificiell intelligens inom Data och IT
Systemvetenskap och AI inom Data och IT

.- Image Acquisition, Synthesis and Enhancement..- Unsupervised Physics-Inspired Shear Wave Speed Estimation in Ultrasound Elastography..- Simplifying Prostate Elastography Using Micro-Ultrasound and Transfer Function Imaging..- Do High-Performance Image-to-Image Translation Networks Enable the Discovery of Radiomic Features? Application to MRI Synthesis from Ultrasound in Prostate Cancer..- PHOCUS: Physics-Based Deconvolution for Ultrasound Resolution Enhancement..- Tracking, Registration and Image-guided Interventions..- PIPsUS: Self-Supervised Point Tracking in Ultrasound..- Structure-aware World Model for Probe Guidance via Large-scale Selfsupervised Pre-train..- An Evaluation of Low-Cost Hardware on 3D Ultrasound Reconstruction Accuracy..- Learning to Match 2D Keypoints Across Preoperative MR and Intraoperative Ultrasound..- Automatic facial axes standardization of 3D fetal ultrasound images..- Segmentation..- C-TRUS: A Novel Dataset and Initial Benchmark For Colon Wall Segmentation in Transabdominal Ultrasound..- Label Dropout: Improved Deep Learning Echocardiography Segmentation Using Multiple Datasets With Domain Shift and Partial Labelling..- Introducing Anatomical Constraints in Mitral Annulus Segmentation in Transesophageal Echocardiography..- Interactive Segmentation Model for Placenta Segmentation from 3D Ultrasound Images..- Enhanced Uncertainty Estimation in Ultrasound Image Segmentation with MSU-Net..- Classification and Detection..- Multi-Site Class-Incremental Learning with Weighted Experts in Echocardiography..- Masked autoencoders for medical ultrasound videos using ROI-aware masking..- Uncertainty-based Multi-modal Learning for Myocardial Infarction Diagnosis using Echocardiography and Electrocardiograms..- Fetal Ultrasound Video Representation Learning using Contrastive Rubik’s Cube Recovery..- LoRIS - Weakly-supervised Anomaly Detection for Ultrasound Images..- Unsupervised Detection of Fetal Brain Anomalies using Denoising Diffusion Models..- Diffusion Models for Unsupervised Anomaly Detection in Fetal Brain Ultrasound.

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Simplifying Medical Ultrasound

5th International Workshop, ASMUS 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings

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