- Kanchana Vaishnavi Gandikota, Paramanand Chandramouli, Hannah Dröge, Michael Möller:
Evaluating Adversarial Robustness of Low dose CT Recovery. MIDL 2023: 1545-1563 - Abdollah Ghazvanchahi, Pejman Jahbedar Maralani, Alan R. Moody, April Khademi:
Effect of Intensity Standardization on Deep Learning for WML Segmentation in Multi-Centre FLAIR MRI. MIDL 2023: 1923-1940 - Monika Grewal, Dustin van Weersel, Henrike Westerveld, Peter A. N. Bosman, Tanja Alderliesten:
Learning Clinically Acceptable Segmentation of Organs at Risk in Cervical Cancer Radiation Treatment from Clinically Available Annotations. MIDL 2023: 260-273 - Hanxue Gu, Hongyu He, Roy J. Colglazier, Jordan Axelrod, Robert French, Maciej A. Mazurowski:
SuperMask: Generating High-resolution object masks from multi-view, unaligned low-resolution MRIs. MIDL 2023: 119-133 - Zijin Gu, Keith Jamison, Amy Kuceyeski, Mert R. Sabuncu:
Decoding natural image stimuli from fMRI data with a surface-based convolutional network. MIDL 2023: 107-118 - Pengfei Guo, Vishal M. Patel:
Reference-based MRI Reconstruction Using Texture Transformer. MIDL 2023: 599-616 - Jiaqi Guo, Emanuel A. Azcona, Santiago Lopez Tapia, Aggelos K. Katsaggelos:
Stage Detection of Mild Cognitive Impairment: Region-dependent Graph Representation Learning on Brain Morphable Meshes. MIDL 2023: 888-904 - Idris Hamoud, Muhammad Abdullah Jamal, Vinkle Srivastav, Didier Mutter, Nicolas Padoy, Omid Mohareri:
ST(OR)2: Spatio-Temporal Object Level Reasoning for Activity Recognition in the Operating Room. MIDL 2023: 1254-1268 - Louis D. van Harten, Rudolf Leonardus Mirjam van Herten, Jaap Stoker, Ivana Isgum:
Deformable Image Registration with Geometry-informed Implicit Neural Representations. MIDL 2023: 730-742 - Johan Fredin Haslum, Christos Matsoukas, Karl-Johan Leuchowius, Erik Müllers, Kevin Smith:
Metadata-guided Consistency Learning for High Content Images. MIDL 2023: 918-936 - Yinsheng He, Xingyu Li:
Whole-slide-imaging Cancer Metastases Detection and Localization with Limited Tumorous Data. MIDL 2023: 877-887 - Rudolf Leonardus Mirjam van Herten, Louis D. van Harten, Nils Planken, Ivana Isgum:
Generative Adversarial Networks for Coronary CT Angiography Acquisition Protocol Correction with Explicit Attenuation Constraints. MIDL 2023: 1288-1303 - Haoxu Huang, Samyak Rawlekar, Sumit Chopra, Cem M. Deniz:
Radiology Reports Improve Visual Representations Learned from Radiographs. MIDL 2023: 1385-1405 - Tianyu Hwang, Chih-Hung Wang, Holger R. Roth, Dong Yang, Can Zhao, Chien-Hua Huang, Weichung Wang:
Semi-supervised Learning with Contrastive and Topology Losses for Catheter Segmentation and Misplacement Prediction. MIDL 2023: 1239-1253 - Jaehwan Jeong, Katherine Tian, Andrew Li, Sina Hartung, Subathra Adithan, Fardad Behzadi, Juan Calle, David Osayande, Michael Pohlen, Pranav Rajpurkar:
Multimodal Image-Text Matching Improves Retrieval-based Chest X-Ray Report Generation. MIDL 2023: 978-990 - Debesh Jha, Nikhil Kumar Tomar, Vanshali Sharma, Ulas Bagci:
TransNetR: Transformer-based Residual Network for Polyp Segmentation with Multi-Center Out-of-Distribution Testing. MIDL 2023: 1372-1384 - Yanni Ji, Marie Cutiongco, Bjørn Sand Jensen, Ke Yuan:
CP2Image: Generating high-quality single-cell images using CellProfiler representations. MIDL 2023: 274-285 - Zongliang Ji, Philip Rosenfield, Christina Eng, Sarah Bettigole, Danielle C. Gibson, Hamid Masoudi, Matthew Hanna, Nicolò Fusi, Kristen A. Severson:
Considerations for data acquisition and modeling strategies: Mitosis detection in computational pathology. MIDL 2023: 1051-1066 - Soodeh Kalaie, Andrew J. Bulpitt, Alejandro F. Frangi, Ali Gooya:
A Geometric Deep Learning Framework for Generation of Virtual Left Ventricles as Graphs. MIDL 2023: 426-443 - Sanaz Karimijafarbigloo, Reza Azad, Amirhossein Kazerouni, Dorit Merhof:
MS-Former: Multi-Scale Self-Guided Transformer for Medical Image Segmentation. MIDL 2023: 680-694 - Sanaz Karimijafarbigloo, Reza Azad, Amirhossein Kazerouni, Saeed Ebadollahi, Dorit Merhof:
MMCFormer: Missing Modality Compensation Transformer for Brain Tumor Segmentation. MIDL 2023: 1144-1162 - Dimitrios Karkalousos, Ivana Isgum, Henk A. Marquering, Matthan W. A. Caan:
MultiTask Learning for accelerated-MRI Reconstruction and Segmentation of Brain Lesions in Multiple Sclerosis. MIDL 2023: 991-1005 - Alexander Ke, Shih-Cheng Huang, Chloe P. O'Connell, Michal Klimont, Serena Yeung, Pranav Rajpurkar:
Video pretraining advances 3D deep learning on chest CT tasks. MIDL 2023: 758-774 - Matthias Keicher, Kamilia Zaripova, Tobias Czempiel, Kristina Mach, Ashkan Khakzar, Nassir Navab:
FlexR: Few-shot Classification with Language Embeddings for Structured Reporting of Chest X-rays. MIDL 2023: 1493-1508 - Heejong Kim, Mert R. Sabuncu:
Learning to Compare Longitudinal Images. MIDL 2023: 350-367 - Nicholas Konz, Maciej A. Mazurowski:
Reverse Engineering Breast MRIs: Predicting Acquisition Parameters Directly from Images. MIDL 2023: 829-845 - Mathieu Labrunie, Daniel Pizarro, Christophe Tilmant, Adrien Bartoli:
Automatic 3D/2D Deformable Registration in Minimally Invasive Liver Resection using a Mesh Recovery Network. MIDL 2023: 1104-1123 - Qian Li, Yunguan Fu, Qianye Yang, Zhijiang Du, Hongjian Yu, Yipeng Hu:
Spatial Correspondence between Graph Neural Network-Segmented Images. MIDL 2023: 1067-1084 - Jun Li, Che Liu, Sibo Cheng, Rossella Arcucci, Shenda Hong:
Frozen Language Model Helps ECG Zero-Shot Learning. MIDL 2023: 402-415 - Cheng Liu, Hisanor Kiryu:
3D Medical Axial Transformer: A Lightweight Transformer Model for 3D Brain Tumor Segmentation. MIDL 2023: 799-813