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ORCID28th MIUA 2024: Manchester, UK - Part I
- Moi Hoon Yap
, Connah Kendrick, Ardhendu Behera, Timothy Cootes, Reyer Zwiggelaar:
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, Ahmed Alshenoudy, Josef Scharinger, Matthias Gmeiner, Stefan Thumfart, Michael Giretzlehner:
Robust Multi-modal Registration of Cerebral Vasculature. 3-18 - Ahmed Alshenoudy, Bertram Sabrowsky-Hirsch, Josef Scharinger, Stefan Thumfart, Michael Giretzlehner:
Towards Segmenting Cerebral Arteries from Structural MRI. 19-33 - Ben Philps, Maria del C. Valdés Hernández, Susana Muñoz Maniega, Mark E. Bastin, Eleni Sakka, Una Clancy, Joanna M. Wardlaw, Miguel O. Bernabeu:
Stochastic Uncertainty Quantification Techniques Fail to Account for Inter-analyst Variability in White Matter Hyperintensity Segmentation. 34-53 - Jaloliddin Rustamov, Zahiriddin Rustamov, Nadia Badawi, Frederic Lesage, Nazar Zaki, Rafat Damseh:
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, Sanjay Kalra, Yee-Hong Yang:
DeepDSMRI: Deep Domain Shift Analyzer for MRI. 81-95 - Dániel Unyi, Bálint Gyires-Tóth:
Self-Supervised Pretraining for Cortical Surface Analysis. 96-108 - Arkadiusz Nowacki, Ewelina Kolpa, Mateusz Szychiewicz, Konrad Ciecierski, Ewa Niewiadomska-Szynkiewicz:
Spike Detection in Deep Brain Stimulation Surgery with Convolutional Neural Networks. 109-121
Medical Images and Computational Models
- Elizabeth Evans, Alyx Elder:
Micro-CT Imaging Techniques for Visualising Pinniped Mystacial Pad Musculature. 125-141 - Krithika Iyer, Jadie Adams, Shireen Y. Elhabian:
SCorP: Statistics-Informed Dense Correspondence Prediction Directly from Unsegmented Medical Images. 142-157 - Zeyu Zhang, Xuyin Qi, Mingxi Chen, Guangxi Li, Ryan Pham, Ayub Qassim, Ella Berry, Zhibin Liao, Owen Siggs, Robert A. McLaughlin, Jamie Craig, Minh-Son To:
JointViT: Modeling Oxygen Saturation Levels with Joint Supervision on Long-Tailed OCTA. 158-172 - Mustapha Zokay, Hicham Saylani:
Identification of Skin Diseases Based on Blind Chromophore Separation and Artificial Intelligence. 173-187 - Chenyu Wang, Vladimir Janjic, Stephen J. McKenna:
Generating Chest Radiology Report Findings Using a Multimodal Method. 188-201 - Lavdie Rada, Inass Azzawi, Preet Kumar, Carlos Brito-Loeza, Cefa Karabag, Constantino Carlos Reyes-Aldasoro:
Image Processing and Machine Learning Techniques for Chagas Disease Detection and Identification. 202-216 - Jakub Mitura, Rafal Józwiak, Jan Mycka, Ihor Mykhalevych, Michal Gonet, Piotr Sobecki, Tomasz Lorenc, Krzysztof Tupikowski:
Ensemble Deep Learning Models for Segmentation of Prostate Zonal Anatomy and Pathologically Suspicious Areas. 217-231 - Lena M. Setterdahl, William R. B. Lionheart, Sean F. Holman, Kyrre Skjerdal, Hunter N. Ratliff, Kristian Smeland Ytre-Hauge, Danny Lathouwers, Ilker Meric:
Image Reconstruction for Proton Therapy Range Verification via U-NETs. 232-244 - Mohammad Areeb Qazi, Ibrahim Almakky, Anees Ur Rehman Hashmi, Santosh Sanjeev, Mohammad Yaqub:
DynaMMo: Dynamic Model Merging for Efficient Class Incremental Learning for Medical Images. 245-257 - Di Fan, Heng Yu, Zhiyuan Xu:
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, Alin Achim, Renata Raele-Rolfe, Qiao Tong, Dylan Bergen, Chrissy L. Hammond, Stephen Cross:
RoTIR: Rotation-Equivariant Network and Transformers for Zebrafish Scale Image Registration. 285-299 - Ayush Roy, Payel Pramanik, Sohom Ghosal, Daria Valenkova, Dmitrii I. Kaplun, Ram Sarkar:
GRU-Net: Gaussian Attention Aided Dense Skip Connection Based MultiResUNet for Breast Histopathology Image Segmentation. 300-313 - Nabeel Khalid, Maria Caroprese, Gillian Lovell, Daniel A. Porto, Johan Trygg, Andreas Dengel, Sheraz Ahmed:
Bounding Box Is All You Need: Learning to Segment Cells in 2D Microscopic Images via Box Annotations. 314-328 - Craig Myles, In Hwa Um, David J. Harrison, David Harris-Birtill:
Leveraging Foundation Models for Enhanced Detection of Colorectal Cancer Biomarkers in Small Datasets. 329-343 - Srijay Deshpande, Durga Parkhi:
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, Abdullah Alsalemi, Shan E Ahmed Raza:
Nuclei-Location Based Point Set Registration of Multi-stained Whole Slide Images. 372-386 - Nabeel Khalid, Mohammadmahdi Koochali, Duway Nicolas Lesmes Leon, Maria Caroprese, Gillian Lovell, Daniel A. Porto, Johan Trygg, Andreas Dengel, Sheraz Ahmed:
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, Céline Thomann, Emma Petiot, Gillian Lovell, Maria Caroprese, Andreas Dengel, Sheraz Ahmed:
A Line Is All You Need: Weak Supervision for 2.5D Cell Segmentation. 402-416
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