- Yiwen Liu, Wenyu Xing, Mingbo Zhao, Mingquan Lin:
An end-to-end framework for diagnosing COVID-19 pneumonia via Parallel Recursive MLP module and Bi-LTSM correlation. MIDL 2023: 416-425 - Mélanie Lubrano, Yaëlle Bellahsen-Harrar, Rutger R. H. Fick, Cécile Badoual, Thomas Walter:
Simple and Efficient Confidence Score for Grading Whole Slide Images. MIDL 2023: 151-169 - Baoqiang Ma, Jiapan Guo, Lisanne van Dijk, Peter M. A. van Ooijen, Stefan Both, Nanna Maria Sijtsema:
TransRP: Transformer-based PET/CT feature extraction incorporating clinical data for recurrence-free survival prediction in oropharyngeal cancer. MIDL 2023: 1640-1654 - Divyam Madaan, Daniel K. Sodickson, Kyunghyun Cho, Sumit Chopra:
On Sensitivity and Robustness of Normalization Schemes to Input Distribution Shifts in Automatic MR Image Diagnosis. MIDL 2023: 1726-1750 - Matthis Manthe, Stefan Duffner, Carole Lartizien:
Whole brain radiomics for clustered federated personalization in brain tumor segmentation. MIDL 2023: 957-977 - NagaGayathri Matcha, Sriprabha Ramanarayanan, Mohammad Al Fahim, Rahul G. S., Keerthi Ram, Mohanasankar Sivaprakasam:
SFT-KD-Recon: Learning a Student-friendly Teacher for Knowledge Distillation in Magnetic Resonance Image Reconstruction. MIDL 2023: 1423-1440 - Raghav Mehta, Changjian Shui, Tal Arbel:
Evaluating the Fairness of Deep Learning Uncertainty Estimates in Medical Image Analysis. MIDL 2023: 1453-1492 - Felix Meissen, Philip Müller, Georgios Kaissis, Daniel Rueckert:
Robust Detection Outcome: A Metric for Pathology Detection in Medical Images. MIDL 2023: 568-585 - Léo Milecki, Vicky Kalogeiton, Sylvain Bodard, Dany Anglicheau, Jean-Michel Correas, Marc-Olivier Timsit, Maria Vakalopoulou:
MEDIMP: 3D Medical Images and clinical Prompts for renal transplant representation learning. MIDL 2023: 846-861 - Ricardo Mokhtari, Azam Hamidinekoo, Daniel James Sutton, Arthur Lewis, Bastian Angermann, Ulf Gehrmann, Pål Lundin, Hibret Adissu, Junmei Cairns, Jessica Neisen, Emon Khan, Daniel Marks, Nia Khachapuridze, Talha Qaiser, Nikolay Burlutskiy:
Interpretable histopathology-based prediction of disease relevant features in Inflammatory Bowel Disease biopsies using weakly-supervised deep learning. MIDL 2023: 479-495 - Vivek Sivaraman Narayanaswamy, Yamen Mubarka, Rushil Anirudh, Deepta Rajan, Andreas Spanias, Jayaraman J. Thiagarajan:
Know Your Space: Inlier and Outlier Construction for Calibrating Medical OOD Detectors. MIDL 2023: 190-211 - Marco Nittscher, Michael Falk Lameter, Riccardo Barbano, Johannes Leuschner, Bangti Jin, Peter Maass:
SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction. MIDL 2023: 617-642 - Rafael Orozco, Mathias Louboutin, Ali Siahkoohi, Gabrio Rizzuti, Tristan van Leeuwen, Felix Johan Herrmann:
Amortized Normalizing Flows for Transcranial Ultrasound with Uncertainty Quantification. MIDL 2023: 332-349 - Yijie Pang, Pujin Cheng, Junyan Lyu, Fan Lin, Xiaoying Tang:
Prior Guided 3D Medical Image Landmark Localization. MIDL 2023: 1163-1175 - Sofia Cardoso Pereira, Joana Rocha, Alex Gaudio, Asim Smailagic, Aurélio Campilho, Ana Maria Mendonça:
Addressing Chest Radiograph Projection Bias in Deep Classification Models. MIDL 2023: 1199-1210 - Nicolas Pinon, Robin Trombetta, Carole Lartizien:
One-Class SVM on siamese neural network latent space for Unsupervised Anomaly Detection on brain MRI White Matter Hyperintensities. MIDL 2023: 1783-1797 - Chinmay Prabhakar, Hongwei Li, Jiancheng Yang, Suprosanna Shit, Benedikt Wiestler, Bjoern H. Menze:
ViT-AE++: Improving Vision Transformer Autoencoder for Self-supervised Medical Image Representations. MIDL 2023: 666-679 - Chinmay Prabhakar, Suprosanna Shit, Johannes C. Paetzold, Ivan Ezhov, Rajat Koner, Hongwei Li, Florian Sebastian Kofler, Bjoern H. Menze:
Vesselformer: Towards Complete 3D Vessel Graph Generation from Images. MIDL 2023: 320-331 - Lemuel Puglisi, Arman Eshaghi, Geoff J. M. Parker, Frederik Barkhof, Daniel C. Alexander, Daniele Ravì:
DeepBrainPrint: A Novel Contrastive Framework for Brain MRI Re-Identification. MIDL 2023: 716-729 - Arnaud Quillent, Vincent Jonas Bismuth, Isabelle Bloch, Christophe Kervazo, Saïd Ladjal:
A deep learning method trained on synthetic data for digital breast tomosynthesis reconstruction. MIDL 2023: 1813-1825 - Febrian Febrian Rachmadi, Charissa Poon, Henrik Skibbe:
Improving Segmentation of Objects with Varying Sizes in Biomedical Images using Instance-wise and Center-of-Instance Segmentation Loss Function. MIDL 2023: 286-300 - Md Mostafijur Rahman, Radu Marculescu:
Multi-scale Hierarchical Vision Transformer with Cascaded Attention Decoding for Medical Image Segmentation. MIDL 2023: 1526-1544 - Gony Rosenman, Itzik Malkiel, Ayam Greental, Talma Hendler, Lior Wolf:
Pre-Training Transformers for Fingerprinting to Improve Stress Prediction in fMRI. MIDL 2023: 212-234 - Shaheer U. Saeed, Tom Syer, Wen Yan, Qianye Yang, Mark Emberton, Shonit Punwani, Matthew John Clarkson, Dean C. Barratt, Yipeng Hu:
Bi-parametric prostate MR image synthesis using pathology and sequence-conditioned stable diffusion. MIDL 2023: 814-828 - Trevor Seets, Wei Lin, Yizhou Lu, Christie Lin, Adam Uselmann, Andreas Velten:
OFDVDnet: A Sensor Fusion Approach for Video Denoising in Fluorescence-Guided Surgery. MIDL 2023: 1564-1580 - Tamir Shor, Tomer Weiss, Dor Noti, Alexander M. Bronstein:
Multi PILOT: Feasible Learned Multiple Acquisition Trajectories For Dynamic MRI. MIDL 2023: 1033-1050 - Attila Simkó, Anders Garpebring, Joakim Jonsson, Tufve Nyholm, Tommy Löfstedt:
Reproducibility of the Methods in Medical Imaging with Deep Learning. MIDL 2023: 95-106 - Nalini M. Singh, Neel Dey, Malte Hoffmann, Bruce Fischl, Elfar Adalsteinsson, Robert Frost, Adrian V. Dalca, Polina Golland:
Data Consistent Deep Rigid MRI Motion Correction. MIDL 2023: 368-381 - Rogier van der Sluijs, Nandita Bhaskhar, Daniel L. Rubin, Curtis P. Langlotz, Akshay S. Chaudhari:
Exploring Image Augmentations for Siamese Representation Learning with Chest X-Rays. MIDL 2023: 444-467 - Joey Spronck, Thijs Gelton, Leander van Eekelen, Joep Bogaerts, Leslie Tessier, Mart van Rijthoven, Lieke van der Woude, Michel van den Heuvel, Willemijn Theelen, Jeroen van der Laak, Francesco Ciompi:
nnUNet meets pathology: Bridging the gap for application to whole slide images and computational biomarkers. MIDL 2023: 1859-1874