default search action
MIDL 2021: Lübeck, Germany
- Mattias P. Heinrich, Qi Dou, Marleen de Bruijne, Jan Lellmann, Alexander Schlaefer, Floris Ernst:
Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany. Proceedings of Machine Learning Research 143, PMLR 2021 - Preface. 1-4
- Christian Abbet, Linda Studer, Andreas Fischer, Heather Dawson, Inti Zlobec, Behzad Bozorgtabar, Jean-Philippe Thiran:
Self-Rule to Adapt: Learning Generalized Features from Sparsely-Labeled Data Using Unsupervised Domain Adaptation for Colorectal Cancer Tissue Phenotyping. 5-21 - Kimberly Amador
, Matthias Wilms, Anthony J. Winder, Jens Fiehler, Nils D. Forkert:
Stroke Lesion Outcome Prediction Based on 4D CT Perfusion Data Using Temporal Convolutional Networks. 22-33 - Lennart Bargsten
Attention via Scattering Transforms for Segmentation of Small Intravascular Ultrasound Data Sets. 34-47 - Mikael Brudfors, Yaël Balbastre, John Ashburner, Geraint Rees, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
An MRF-UNet Product of Experts for Image Segmentation. 48-59 - Tianshu Chu, Xinmeng Li, Huy V. Vo, Ronald M. Summers, Elena Sizikova:
Improving Weakly Supervised Lesion Segmentation using Multi-Task Learning. 60-73 - Joseph Paul Cohen, Rupert Brooks, Sovann En, Evan Zucker, Anuj Pareek, Matthew P. Lungren, Akshay Chaudhari:
Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Counterfactual Generation for Chest X-rays. 74-104 - Steffen Czolbe, Oswin Krause, Aasa Feragen
Semantic similarity metrics for learned image registration. 105-118 - Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman:
M-GCN: A Multimodal Graph Convolutional Network to Integrate Functional and Structural Connectomics Data to Predict Multidimensional Phenotypic Characterizations. 119-130 - Matteo Dunnhofer, Niki Martinel, Christian Micheloni:
Improving MRI-based Knee Disorder Diagnosis with Pyramidal Feature Details. 131-147 - Oleh Dzyubachyk, Roman I Koning, Aat A. Mulder, M. Christina Avramut, Frank G. A. Faas, Abraham J. Koster:
Intensity Correction and Standardization for Electron Microscopy Data. 148-157 - Rosana El Jurdi
A Surprisingly Effective Perimeter-based Loss for Medical Image Segmentation. 158-167 - Khrystyna Faryna, Jeroen van der Laak, Geert Litjens:
Tailoring automated data augmentation to H&E-stained histopathology. 168-178 - Chao Feng, Chad M. Vanderbilt, Thomas J. Fuchs:
Nuc2Vec: Learning Representations of Nuclei in Histopathology Images with Contrastive Loss. 179-189 - Soham Uday Gadgil
CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray Segmentation. 190-204 - Camila González, Anirban Mukhopadhyay:
Self-supervised Out-of-distribution Detection for Cardiac CMR Segmentation. 205-218 - Philipp Grüning, Falk Nette, Noah Heldt, Ana Cristina Guerra de Souza, Erhardt Barth:
Direct Inference of Cell Positions using Lens-Free Microscopy and Deep Learning. 219-227 - Umang Gupta, Dimitris Stripelis, Pradeep K. Lam, Paul M. Thompson, José Luis Ambite, Greg Ver Steeg:
Membership Inference Attacks on Deep Regression Models for Neuroimaging. 228-251 - Jannis Hagenah, Floris Ernst:
Discrete Pseudohealthy Synthesis: Aortic Root Shape Typification and Type Classification with Pathological Prior. 252-267 - Qian He, Shuailin Li, Xuming He:
Weakly Supervised Volumetric Segmentation via Self-taught Shape Denoising Model. 268-285 - Matthäus Heer, Janis Postels, Xiaoran Chen, Ender Konukoglu, Shadi Albarqouni:
The OOD Blind Spot of Unsupervised Anomaly Detection. 286-300 - Sobhan Hemati, Shivam Kalra, Cameron Meaney, Morteza Babaie, Ali Ghodsi, Hamid R. Tizhoosh:
CNN and Deep Sets for End-to-End Whole Slide Image Representation Learning. 301-311 - Alessa Hering, Felix Peisen, Teresa Amaral, Sergios Gatidis, Thomas Eigentler, Ahmed Othman, Jan Hendrik Moltz:
Whole-Body Soft-Tissue Lesion Tracking and Segmentation in Longitudinal CT Imaging Studies. 312-326 - Xiaobin Hu, Yanyang Yan, Wenqi Ren, Hongwei Li, Amirhossein Bayat, Yu Zhao, Bjoern H. Menze:
Feedback Graph Attention Convolutional Network for MR Images Enhancement by Exploring Self-Similarity Features. 327-337 - Fahdi Kanavati, Masayuki Tsuneki:
Partial transfusion: on the expressive influence of trainable batch norm parameters for transfer learning. 338-353 - Hoel Kervadec, Houda Bahig, Laurent Létourneau-Guillon, Jose Dolz, Ismail Ben Ayed:
Beyond pixel-wise supervision for segmentation: A few global shape descriptors might be surprisingly good! 354-368 - Andreas M. Kist, Julian Zilker, Michael Döllinger, Marion Semmler:
Feature-based image registration in structured light endoscopy. 369-383 - Aishik Konwer, Joseph Bae, Gagandeep Singh, Rishabh Gattu, Syed Ali, Jeremy Green, Tej Phatak, Amit Gupta, Chao Chen, Joel H. Saltz, Prateek Prasanna:
Predicting COVID-19 Lung Infiltrate Progression on Chest Radiographs Using Spatio-temporal LSTM based Encoder-Decoder Network. 384-398 - Manan Lalit, Pavel Tomancak, Florian Jug:
Embedding-based Instance Segmentation in Microscopy. 399-415 - Andréanne Lemay, Charley Gros, Olivier Vincent, Yaou Liu, Joseph Paul Cohen, Julien Cohen-Adad:
Benefits of Linear Conditioning for Segmentation using Metadata. 416-430 - Juan Liu:
Improved model-based deep learning for quantitative susceptibility mapping. 431-450 - Kangning Liu, Yiqiu Shen, Nan Wu, Jakub Piotr Chledowski, Carlos Fernandez-Granda, Krzysztof J. Geras:
Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosis. 451-472 - Harsh Maheshwari, Vidit Goel, Ramanathan Sethuraman, Debdoot Sheet:
Distill DSM: Computationally efficient method for segmentation of medical imaging volumes. 473-483 - Dominik Mairhöfer, Manuel Laufer, Paul Martin Simon, Malte Sieren, Arpad Bischof, Thomas Käster, Erhardt Barth, Jörg Barkhausen, Thomas Martinetz:
An AI-based Framework for Diagnostic Quality Assessment of Ankle Radiographs. 484-496 - Pauline Mouches, Matthias Wilms, Deepthi Rajashekar, Sönke Langner, Nils Daniel Forkert:
Unifying Brain Age Prediction and Age-Conditioned Template Generation with a Deterministic Autoencoder. 497-506 - Raouf Muhamedrahimov, Amir Bar, Ayelet Akselrod-Ballin:
Learning Interclass Relations for Intravenous Contrast Phase Classification in CT. 507-519 - Hassan Muhammad, Chensu Xie, Carlie S. Sigel, Michael Doukas, Lindsay Alpert, Amber Lea Simpson, Thomas J. Fuchs:
EPIC-Survival: End-to-end Part Inferred Clustering for Survival Analysis, with Prognostic Stratification Boosting. 520-531 - Daniel Neimark, Omri Bar, Maya Zohar, Gregory D. Hager, Dotan Asselmann:
"Train one, Classify one, Teach one" - Cross-surgery transfer learning for surgical step recognition. 532-544 - Chanh Nguyen, Minh-Thanh Huynh, Minh Quan Tran, Ngoc Hoang Nguyen, Mudit Jain, Van Doan Ngo, Tan Duc Vo, Trung H. Bui, Steven Quoc Hung Truong:
GOAL: Gist-set Online Active Learning for Efficient Chest X-ray Image Annotation. 545-553 - Antoine Olivier, Caroline Raynaud:
Balanced sampling for an object detection problem - application to fetal anatomies detection. 554-566 - Caner Özer, Ilkay Öksüz:
Explainable Image Quality Analysis of Chest X-Rays. 567-580 - Markus Philipp, Anna Alperovich, Marielena Gutt-Will, Andrea Mathis, Stefan Saur, Andreas Raabe, Franziska Mathis-Ullrich:
Localizing Neurosurgical Instruments Across Domains and in the Wild. 581-595 - Walter Hugo Lopez Pinaya, Petru-Daniel Tudosiu, Robert J. Gray, Geraint Rees, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Unsupervised Brain Anomaly Detection and Segmentation with Transformers. 596-617 - Carolin M. Pirkl, Matteo Cencini, Jan W. Kurzawski, Diana Waldmannstetter, Hongwei Li, Anjany Sekuboyina, Sebastian Endt, Luca Peretti, Graziella Donatelli, Rosa Pasquariello, Michela Tosetti, Mauro Costagli, Guido Buonincontri, Marion I. Menzel, Bjoern H. Menze:
Residual learning for 3D motion corrected quantitative MRI: Robust clinical T1, T2 and proton density mapping. 618-632 - Juan-Carlos Prieto, Hina Shah, Kasey Jones, Robert F. Chew, Hashiya M. Kana, Jerusha Weaver, Rebecca M. Flueckiger, Scott McPherson, Emily W. Gower:
Image Sequence Generation and Analysis via GRU and Attention for Trachomatous Trichiasis Classification. 633-644 - Huaqi Qiu, Chen Qin, Andreas Schuh, Kerstin Hammernik, Daniel Rueckert:
Learning Diffeomorphic and Modality-invariant Registration using B-splines. 645-664 - Abhejit Rajagopal, Vamshi Chowdary Madala, Thomas A. Hope, Peder E. Z. Larson:
Understanding and Visualizing Generalization in UNets. 665-681 - Yash Sharma, Aman Shrivastava, Lubaina Ehsan, Christopher A. Moskaluk, Sana Syed, Donald E. Brown:
Cluster-to-Conquer: A Framework for End-to-End Multi-Instance Learning for Whole Slide Image Classification. 682-698 - Siyu Shi, Ishaan Malhi, Kevin Tran, Andrew Y. Ng, Pranav Rajpurkar:
Unseen Disease Detection for Deep Learning Interpretation of Chest X-rays. 699-712 - Attila Tibor Simkó, Tommy Löfstedt, Anders Garpebring, Mikael Bylund, Tufve Nyholm, Joakim Jonsson:
Changing the Contrast of Magnetic Resonance Imaging Signals using Deep Learning. 713-727 - Hari Sowrirajan, Jingbo Yang, Andrew Y. Ng, Pranav Rajpurkar:
MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models. 728-744 - Malte Tölle, Max-Heinrich Laves, Alexander Schlaefer:
A Mean-Field Variational Inference Approach to Deep Image Prior for Inverse Problems in Medical Imaging. 745-760 - Md Asadullah Turja, Guorong Wu, Defu Yang, Martin Andreas Styner:
Learning the Latent Heat Diffusion Process through Structural Brain Network from Longitudinal β-Amyloid Data. 761-773 - Hristina Uzunova, Heinz Handels, Jan Ehrhardt:
Guided Filter Regularization for Improved Disentanglement of Shape and Appearance in Diffeomorphic Autoencoders. 774-786 - Saverio Vadacchino, Raghav Mehta, Nazanin Mohammadi Sepahvand, Brennan Nichyporuk, James J. Clark, Tal Arbel:
HAD-Net: A Hierarchical Adversarial Knowledge Distillation Network for Improved Enhanced Tumour Segmentation Without Post-Contrast Images. 787-801 - Louis D. van Harten, Catharina S. de Jonge, Jaap Stoker, Ivana Isgum:
Untangling the Small Intestine in 3D cine-MRI using Deep Stochastic Tracking. 802-812 - David A. Wood, Sina Kafiabadi, Aisha Al Busaidi, Emily Guilhem, Antanas Montvila, Siddharth Agarwal, Jeremy Lynch, Matthew Townend, Gareth J. Barker, Sébastien Ourselin, James H. Cole, Thomas C. Booth:
Automated triaging of head MRI examinations using convolutional neural networks. 813-841 - Hongrun Zhang, Yanda Meng
A regularization term for slide correlation reduction in whole slide image analysis with deep learning. 842-854 - Bokai Zhang, Amer Ghanem, Alexander Simes, Henry Choi, Andrew Yoo, Andrew Min:
SWNet: Surgical Workflow Recognition with Deep Convolutional Network. 855-869 - Jinwei Zhang, Hang Zhang, Pascal Spincemaille, Thanh D. Nguyen, Mert R. Sabuncu, Yi Wang:
Hybrid optimization between iterative and network fine-tuning reconstructions for fast quantitative susceptibility mapping. 870-880
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2024-11-15 19:43 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: