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28th MIUA 2024: Manchester, UK - Part I
- Moi Hoon Yap
, Connah Kendrick
Medical Image Understanding and Analysis - 28th Annual Conference, MIUA 2024, Manchester, UK, July 24-26, 2024, Proceedings, Part I. Lecture Notes in Computer Science 14859, Springer 2024, ISBN 978-3-031-66954-5
Advancement in Brain Imaging
- Bertram Sabrowsky-Hirsch
Robust Multi-modal Registration of Cerebral Vasculature. 3-18 - Ahmed Alshenoudy
Towards Segmenting Cerebral Arteries from Structural MRI. 19-33 - Ben Philps
Stochastic Uncertainty Quantification Techniques Fail to Account for Inter-analyst Variability in White Matter Hyperintensity Segmentation. 34-53 - Jaloliddin Rustamov, Zahiriddin Rustamov
Learning-Based MRI Response Predictions from OCT Microvascular Models to Replace Simulation-Based Frameworks. 54-67 - Lan Jiang, Yuchao Zheng, Miao Yu, Haiqing Zhang, Fatemah Aladwani, Alessandro Perelli
Multimodal 3D Brain Tumor Segmentation with Adversarial Training and Conditional Random Field. 68-80 - Rafsanjany Kushol
DeepDSMRI: Deep Domain Shift Analyzer for MRI. 81-95 - Dániel Unyi
Self-Supervised Pretraining for Cortical Surface Analysis. 96-108 - Arkadiusz Nowacki
Spike Detection in Deep Brain Stimulation Surgery with Convolutional Neural Networks. 109-121
Medical Images and Computational Models
- Elizabeth Evans
Micro-CT Imaging Techniques for Visualising Pinniped Mystacial Pad Musculature. 125-141 - Krithika Iyer
SCorP: Statistics-Informed Dense Correspondence Prediction Directly from Unsegmented Medical Images. 142-157 - Zeyu Zhang
JointViT: Modeling Oxygen Saturation Levels with Joint Supervision on Long-Tailed OCTA. 158-172 - Mustapha Zokay
Identification of Skin Diseases Based on Blind Chromophore Separation and Artificial Intelligence. 173-187 - Chenyu Wang
Generating Chest Radiology Report Findings Using a Multimodal Method. 188-201 - Lavdie Rada
Image Processing and Machine Learning Techniques for Chagas Disease Detection and Identification. 202-216 - Jakub Mitura
Ensemble Deep Learning Models for Segmentation of Prostate Zonal Anatomy and Pathologically Suspicious Areas. 217-231 - Lena M. Setterdahl
Image Reconstruction for Proton Therapy Range Verification via U-NETs. 232-244 - Mohammad Areeb Qazi
DynaMMo: Dynamic Model Merging for Efficient Class Incremental Learning for Medical Images. 245-257 - Di Fan
PDSE: A Multiple Lesion Detector for CT Images Using PANet and Deformable Squeeze-and-Excitation Block. 258-266 - Muhammad Osama Khan, Yi Fang:
What Is the Best Way to Fine-Tune Self-supervised Medical Imaging Models? 267-281
Digital Pathology, Histology and Microscopic Imaging
- Ruixiong Wang
RoTIR: Rotation-Equivariant Network and Transformers for Zebrafish Scale Image Registration. 285-299 - Ayush Roy
GRU-Net: Gaussian Attention Aided Dense Skip Connection Based MultiResUNet for Breast Histopathology Image Segmentation. 300-313 - Nabeel Khalid
Bounding Box Is All You Need: Learning to Segment Cells in 2D Microscopic Images via Box Annotations. 314-328 - Craig Myles
Leveraging Foundation Models for Enhanced Detection of Colorectal Cancer Biomarkers in Small Datasets. 329-343 - Srijay Deshpande
SPADESegResNet: Harnessing Spatially-Adaptive Normalization for Breast Cancer Semantic Segmentation. 344-356 - Yu-Chen Lai, Wei-Ta Chu:
Unsupervised Anomaly Detection on Histopathology Images Using Adversarial Learning and Simulated Anomaly. 357-371 - Adith Jeyasangar
Nuclei-Location Based Point Set Registration of Multi-stained Whole Slide Images. 372-386 - Nabeel Khalid
CellGenie: An End-to-End Pipeline for Synthetic Cellular Data Generation and Segmentation: A Use Case for Cell Segmentation in Microscopic Images. 387-401 - Fabian Schmeisser
A Line Is All You Need: Weak Supervision for 2.5D Cell Segmentation. 402-416
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