default search action
MIDL 2022: Zurich, Switzerland
- Ender Konukoglu, Bjoern H. Menze, Archana Venkataraman, Christian F. Baumgartner, Qi Dou, Shadi Albarqouni:
International Conference on Medical Imaging with Deep Learning, MIDL 2022, 6-8 July 2022, Zurich, Switzerland. Proceedings of Machine Learning Research 172, PMLR 2022 - Preface. 1-4
- Ameen Ali, Tal Shaharabany, Lior Wolf:
Explainability Guided COVID-19 Detection in CT Scans. 5-21 - Tamaz Amiranashvili, David Lüdke, Hongwei Bran Li, Bjoern H. Menze, Stefan Zachow:
Learning Shape Reconstruction from Sparse Measurements with Neural Implicit Functions. 22-34 - Muhammad Asad, Lucas Fidon, Tom Vercauteren:
ECONet: Efficient Convolutional Online Likelihood Network for Scribble-based Interactive Segmentation. 35-47 - Reza Azad, Nika Khosravi, Dorit Merhof:
SMU-Net: Style matching U-Net for brain tumor segmentation with missing modalities. 48-62 - Tim Bakker, Matthew J. Muckley, Adriana Romero-Soriano, Michal Drozdzal, Luis Pineda:
On learning adaptive acquisition policies for undersampled multi-coil MRI reconstruction. 63-85 - Mathieu G. G. Bartels, Ivona Najdenkoska, Rutger R. van de Leur, Arjan Sammani, Karim Taha, David M. Knigge, Pieter A. F. M. Doevendans, Marcel Worring, René van Es:
Learning to Automatically Generate Accurate ECG Captions. 86-102 - Soufiane Belharbi, Marco Pedersoli, Ismail Ben Ayed, Luke McCaffrey, Eric Granger:
Negative Evidence Matters in Interpretable Histology Image Classification. 103-129 - Benjamin Bergner, Csaba Rohrer, Aiham Taleb, Martha Duchrau, Guilherme De Leon, Jonas Almeida Rodrigues, Falk Schwendicke, Joachim Krois, Christoph Lippert:
Interpretable and Interactive Deep Multiple Instance Learning for Dental Caries Classification in Bitewing X-rays. 130-149 - Jules Berman, Dmitri B. Chklovskii, Jingpeng Wu:
Bridging the Gap: Point Clouds for Merging Neurons in Connectomics. 150-159 - Florentin Bieder, Julia Wolleb, Robin Sandkühler, Philippe C. Cattin:
Position Regression for Unsupervised Anomaly Detection. 160-172 - Alexander Bigalke, Lasse Hansen, Jasper Diesel, Mattias P. Heinrich:
Domain adaptation through anatomical constraints for 3d human pose estimation under the cover. 173-187 - Robin Camarasa, Hoel Kervadec, Daniel Bos, Marleen de Bruijne:
Differentiable Boundary Point Extraction for Weakly Supervised Star-shaped Object Segmentation. 188-198 - João B. S. Carvalho, João A. Santinha, Djordje Miladinovic, Carlos Cotrini, Joachim M. Buhmann:
Holistic Modeling In Medical Image Segmentation Using Spatial Recurrence. 199-218 - Krishna Chaitanya, Chloé Audigier, Laura Elena Balascuta, Tommaso Mansi:
Automatic planning of liver tumor thermal ablation using deep reinforcement learning. 219-230 - Joseph Paul Cohen, Joseph D. Viviano, Paul Bertin, Paul Morrison, Parsa Torabian, Matteo Guarrera, Matthew P. Lungren, Akshay Chaudhari, Rupert Brooks, Mohammad Hashir, Hadrien Bertrand:
TorchXRayVision: A library of chest X-ray datasets and models. 231-249 - Pedro Costa, Alex Gaudio
, Aurélio Campilho, Jaime S. Cardoso:
Explainable Weakly-Supervised Cell Segmentation by Canonical Shape Learning and Transformation. 250-260 - Jeff Craley, Emily Johnson, Christophe Jouny, David Hsu, Raheel Ahmed, Archana Venkataraman:
SZLoc: A Multi-resolution Architecture for Automated Epileptic Seizure Localization from Scalp EEG. 261-281 - Simon Dahan, Abdulah Fawaz, Logan Z. J. Williams, Chunhui Yang, Timothy S. Coalson, Matthew F. Glasser, A. David Edwards, Daniel Rueckert, Emma C. Robinson:
Surface Vision Transformers: Attention-Based Modelling applied to Cortical Analysis. 282-303 - Ruining Deng, Quan Liu, Can Cui, Zuhayr Asad, Haichun Yang, Yuankai Huo:
Single Dynamic Network for Multi-label Renal Pathology Image Segmentation. 304-314 - Felix Denzinger, Michael Wels, Oliver Taubmann, Mehmet A. Gülsün, Max Schöbinger, Florian André, Sebastian J. Buss, Johannes Görich, Michael Sühling, Andreas K. Maier:
CAD-RADS Scoring using Deep Learning and Task-Specific Centerline Labeling. 315-324 - Arjun D. Desai, Beliz Gunel, Batu M. Ozturkler, Harris Beg, Shreyas Vasanawala, Brian A. Hargreaves, Christopher Ré, John M. Pauly, Akshay S. Chaudhari:
VORTEX: Physics-Driven Data Augmentations Using Consistency Training for Robust Accelerated MRI Reconstruction. 325-352 - Andrei Dmitrenko, Mauro M. Masiero, Nicola Zamboni:
Comparing representations of biological data learned with different AI paradigms, augmenting and cropping strategies. 353-369 - Andrei Dmitrenko, Mauro M. Masiero, Nicola Zamboni:
Self-supervised learning for analysis of temporal and morphological drug effects in cancer cell imaging data. 370-386 - Joshua Durso-Finley, Jean-Pierre R. Falet, Brennan Nichyporuk, Douglas L. Arnold, Tal Arbel:
Personalized Prediction of Future Lesion Activity and Treatment Effect in Multiple Sclerosis from Baseline MRI. 387-406 - Moritz Fuchs
Practical uncertainty quantification for brain tumor segmentation. 407-422 - Lucy Godson, Navid Alemi Koohbanani, Jeremie Nsengimana, Graham P. Cook, Emily L. Clarke, Darren Treanor, D. Timothy Bishop, Julia Newton-Bishop, Ali Gooya:
Weakly-supervised learning for image-based classification of primary melanomas into genomic immune subgroups. 423-440 - Karol Gotkowski
i3Deep: Efficient 3D interactive segmentation with the nnU-Net. 441-456 - Mark S. Graham, Petru-Daniel Tudosiu, Paul Wright, Walter Hugo Lopez Pinaya, Jean-Marie U.-King-Im, Yee H. Mah, James T. Teo, Hans Rolf Jäger, David Werring, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Transformer-based out-of-distribution detection for clinically safe segmentation. 457-476 - Huaqing He, Li Lin, Zhiyuan Cai, Xiaoying Tang:
JOINED : Prior Guided Multi-task Learning for Joint Optic Disc/Cup Segmentation and Fovea Detection. 477-492 - Xiaoxuan He, Hualiang Wang, Haoji Hu, Jianfei Yang, Yang Feng, Gaoang Wang, Zuozhu Liu:
Unsupervised Pre-training Improves Tooth Segmentation in 3-Dimensional Intraoral Mesh Scans. 493-507 - Andrew Hoopes, Juan Eugenio Iglesias, Bruce Fischl, Douglas N. Greve, Adrian V. Dalca:
TopoFit: Rapid Reconstruction of Topologically-Correct Cortical Surfaces. 508-520 - Timo Horstmann, Oliver Zettinig, Wolfgang Wein, Raphael Prevost:
Orientation Estimation of Abdominal Ultrasound Images with Multi-Hypotheses Networks. 521-534 - Mohammad Reza Hosseinzadeh Taher, Fatemeh Haghighi, Michael B. Gotway, Jianming Liang:
CAiD: Context-Aware Instance Discrimination for Self-supervised Learning in Medical Imaging. 535-551 - Dewei Hu, Hao Li, Han Liu, Ipek Oguz:
Domain Generalization for Retinal Vessel Segmentation with Vector Field Transformer. 552-564 - Chaoxing Huang
Breathing Freely: Self-supervised Liver T1rho Mapping from A Single T1rho-weighted Image. 565-575 - Ziyan Huang, Zehua Wang, Zhikai Yang, Lixu Gu:
AdwU-Net: Adaptive Depth and Width U-Net for Medical Image Segmentation by Differentiable Neural Architecture Search. 576-589 - Justin Huynh, Samira Masoudi, Abraham Noorbakhsh, Kyle Hasenstab, Michael J. Pazzani, Albert Hsiao:
Deep Learning Radiographic Assessment of Pulmonary Edema: Training with Serum Biomarkers. 590-604 - Ankita Joshi
Diffeomorphic Image Registration Using Lipschitz Continuous Residual Networks. 605-617 - Xuan Kan, Hejie Cui
FBNETGEN: Task-aware GNN-based fMRI Analysis via Functional Brain Network Generation. 618-637 - Frederic Kanter, Jan Lellmann:
A Flexible Meta Learning Model for Image Registration. 638-652 - Antanas Kascenas, Nicolas Pugeault, Alison Q. O'Neil:
Denoising Autoencoders for Unsupervised Anomaly Detection in Brain MRI. 653-664 - Victoriya Kashtanova, Ibrahim Ayed, Andony Arrieula, Mark Potse, Patrick Gallinari, Maxime Sermesant:
Deep Learning for Model Correction in Cardiac Electrophysiological Imaging. 665-675 - HyunWoo Kim, Hanbin Ko, JungJun Kim:
PILLET-GAN: Pixel-Level Lesion Traversal Generative Adversarial Network for Pneumonia Localization. 676-688 - Lukas Klein, João B. S. Carvalho, Mennatallah El-Assady, Paolo Penna, Joachim M. Buhmann, Paul F. Jaeger:
Improving Explainability of Disentangled Representations using Multipath-Attribution Mappings. 689-712 - Tobias Knopp, Mirco Grosser:
Warmstart Approach for Accelerating Deep Image Prior Reconstruction in Dynamic Tomography. 713-725 - Lisa M. Koch, Christian M. Schürch, Arthur Gretton, Philipp Berens:
Hidden in Plain Sight: Subgroup Shifts Escape OOD Detection. 726-740 - Farina Kock, Felix Thielke, Grzegorz Chlebus, Hans Meine:
Confidence Histograms for Model Reliability Analysis and Temperature Calibration. 741-759 - Lars Leyendecker, Julius Haas, Tobias Piotrowski, Maik Frye, Cora Becker, Bernd K. Fleischmann, Michael Hesse, Robert H. Schmitt:
A Modular Deep Learning Pipeline for Cell Culture Analysis: Investigating the Proliferation of Cardiomyocytes. 760-773 - Kang Lin, Reinhard Heckel:
Vision Transformers Enable Fast and Robust Accelerated MRI. 774-795 - Jingya Liu, Bin Lou, Mamadou Diallo, Tongbai Meng, Heinrich von Busch, Robert Grimm, Yingli Tian, Dorin Comaniciu, Ali Kamen:
Detecting Out-of-Distribution via an Unsupervised Uncertainty Estimation for Prostate Cancer Diagnosis. 796-807 - Haozhe Luo, Changdong Yu, Raghavendra Selvan:
Hybrid Ladder Transformers with Efficient Parallel-Cross Attention for Medical Image Segmentation. 808-819 - Xiangde Luo, Minhao Hu
Semi-Supervised Medical Image Segmentation via Cross Teaching between CNN and Transformer. 820-833 - Matthew Lyon, Paul A. Armitage, Mauricio A. Álvarez:
Angular Super-Resolution in Diffusion MRI with a 3D Recurrent Convolutional Autoencoder. 834-846 - Tianyu Ma, Benjamin C. Lee, Mert R. Sabuncu:
Label conditioned segmentation. 847-857 - Dwarikanath Mahapatra, Zongyuan Ge:
MR Image Super Resolution By Combining Feature Disentanglement CNNs and Vision Transformers. 858-878 - Danial Maleki, Hamid R. Tizhoosh:
LILE: Look In-Depth before Looking Elsewhere - A Dual Attention Network using Transformers for Cross-Modal Information Retrieval in Histopathology Archives. 879-894 - Itzik Malkiel, Gony Rosenman, Lior Wolf, Talma Hendler:
Self-Supervised Transformers for fMRI representation. 895-913 - Felix Meissen, Benedikt Wiestler, Georgios Kaissis, Daniel Rueckert:
On the Pitfalls of Using the Residual Error as Anomaly Score. 914-928 - Valentin Oreiller, Julien Fageot, Vincent Andrearczyk, John O. Prior, Adrien Depeursinge
Robust Multi-Organ Nucleus Segmentation Using a Locally Rotation Invariant Bispectral U-Net. 929-943 - Oscar Pina, Irene Cumplido-Mayoral, Raffaele Cacciaglia, José María González-de-Echávarri, Juan Domingo Gispert, Verónica Vilaplana:
Structural Networks for Brain Age Prediction. 944-960 - Navid Rabbani, Callyane Sève-d'Erceville, Nicolas Bourdel, Adrien Bartoli:
Video-based Computer-aided Laparoscopic Bleeding Management: a Space-time Memory Neural Network with Positional Encoding and Adversarial Domain Adaptation. 961-974 - Ekaterina Redekop, Karthik V. Sarma, Adam Kinnaird, Anthony Sisk, Steven S. Raman, Leonard S. Marks, William Speier, Corey W. Arnold:
Attention-Guided Prostate Lesion Localization and Grade Group Classification with Multiple Instance Learning. 975-987 - Saikat Roy
Are 2.5D approaches superior to 3D deep networks in whole brain segmentation? 988-1004 - Numan Saeed, Shahad Hardan, Kudaibergen Abutalip, Mohammad Yaqub:
Is it Possible to Predict MGMT Promoter Methylation from Brain Tumor MRI Scans using Deep Learning Models? 1005-1018 - Pranab Samanta, Nitin Singhal:
YAMU: Yet Another Modified U-Net Architecture for Semantic Segmentation. 1019-1033 - Julien Schroeter, Chelsea Myers-Colet, Douglas L. Arnold, Tal Arbel:
Segmentation-Consistent Probabilistic Lesion Counting. 1034-1056 - Ahmed H. Shahin, Joseph Jacob, Daniel C. Alexander, David Barber:
Survival Analysis for Idiopathic Pulmonary Fibrosis using CT Images and Incomplete Clinical Data. 1057-1074 - Ziyao Shang, Md Asadullah Turja, Eric Feczko, Audrey Houghton, Amanda Rueter, Lucille A Moore, Kathy Snider, Timothy Hendrickson, Paul Reiners, Sally Stoyell, Omid Kardan, Monica Rosenberg, Jed T. Elison, Damien A. Fair, Martin A. Styner:
Learning Strategies for Contrast-agnostic Segmentation via SynthSeg for Infant MRI data. 1075-1084 - Kuruparan Shanmugalingam, Arcot Sowmya, Daniel Aaron Moses, Erik Meijering:
Attention Guided Deep Supervision Model for Prostate Segmentation in Multisite Heterogeneous MRI Data. 1085-1095 - Rasha Sheikh, Thomas Schultz:
Unsupervised Domain Adaptation for Medical Image Segmentation via Self-Training of Early Features. 1096-1107 - Daniel Siegismund, Mario Wieser, Stephan Heyse, Stephan Steigele:
Self-Supervised Representation Learning for High-Content Screening. 1108-1124 - Attila Simkó, Tommy Löfstedt, Anders Garpebring, Tufve Nyholm, Joakim Jonsson:
MRI bias field correction with an implicitly trained CNN. 1125-1138 - Rohit Singla, Cailin Ringstrom, Ricky Hu, Victoria A. Lessoway, Janice Reid, Robert Rohling, Christopher Y. Nguan:
Speckle and Shadows: Ultrasound-specific Physics-based Data Augmentation for Kidney Segmentation. 1139-1148 - Ikboljon Sobirov
Automatic Segmentation of Head and Neck Tumor: How Powerful Transformers Are? 1149-1161 - Xinzi Sun, Dechun Wang, Qilei Chen, Jing Ni, Shuijiao Chen, Xiaowei Liu, Yu Cao, Benyuan Liu:
MAF-Net: Multi-branch Anchor-Free Detector for Polyp Localization and Classification in Colonoscopy. 1162-1172 - Anna Klimovskaia Susmelj, Berkan Lafci, Firat Ozdemir, Neda Davoudi
Signal Domain Learning Approach for Optoacoustic Image Reconstruction from Limited View Data. 1173-1191 - Devavrat Tomar, Guillaume Vray, Jean-Philippe Thiran, Behzad Bozorgtabar
OptTTA: Learnable Test-Time Augmentation for Source-Free Medical Image Segmentation Under Domain Shift. 1192-1217 - Clara Tomasini, Iñigo Alonso, Luis Riazuelo, Ana C. Murillo:
Efficient tool segmentation for endoscopic videos in the wild. 1218-1234 - Masayuki Tsuneki, Fahdi Kanavati:
Inference of captions from histopathological patches. 1235-1250 - Serban Vadineanu, Daniël Maria Pelt, Oleh Dzyubachyk, Kees Joost Batenburg:
An Analysis of the Impact of Annotation Errors on the Accuracy of Deep Learning for Cell Segmentation. 1251-1267 - Serge Vasylechko Didenko, Simon K. Warfield, Sila Kurugol, Onur Afacan:
SynthMap: a generative model for synthesis of 3D datasets for quantitative MRI parameter mapping of myelin water fraction. 1268-1284 - Boyko Vodenicharski, Samuel McDermott, Katherine M. Webber, Viola Introini, Pietro Cicuta, Richard W. Bowman, Ivor J. A. Simpson, Neill D. F. Campbell:
Cell Anomaly Localisation using Structured Uncertainty Prediction Networks. 1285-1300 - Damir Vrabac, Akshay Smit, Yujie He, Andrew Y. Ng, Andrew L. Beam, Pranav Rajpurkar:
MedSelect: Selective Labeling for Medical Image Classification Using Meta-Learning. 1301-1310 - Royden Wagner, Karl Rohr:
EfficientCellSeg: Efficient Volumetric Cell Segmentation Using Context Aware Pseudocoloring. 1311-1321 - Yuan Wang, Laura Blackie, Irene Miguel-Aliaga, Wenjia Bai:
Memory-efficient Segmentation of High-resolution Volumetric MicroCT Images. 1322-1335 - Julia Wolleb, Robin Sandkühler, Florentin Bieder, Philippe Valmaggia, Philippe C. Cattin:
Diffusion Models for Implicit Image Segmentation Ensembles. 1336-1348 - Jelmer M. Wolterink, Jesse C. Zwienenberg, Christoph Brune:
Implicit Neural Representations for Deformable Image Registration. 1349-1359 - Boyeong Woo, Craig Engstrom, Jurgen Fripp, Stuart Crozier, Shekhar S. Chandra:
Anomaly-Aware 3D Segmentation of Knee Magnetic Resonance Images. 1360-1374 - Jiqing Wu, Inti Zlobec, Maxime W. Lafarge, Yukun He, Viktor H. Koelzer:
Towards IID representation learning and its application on biomedical data. 1375-1402 - Bingyu Xin, Timothy S. Phan, Leon Axel, Dimitris N. Metaxas:
Learned Half-Quadratic Splitting Network for MR Image Reconstruction. 1403-1412 - Mou-Cheng Xu, Yukun Zhou, Chen Jin, Stefano B. Blumberg, Frederick J. Wilson, Marius de Groot, Daniel C. Alexander, Neil P. Oxtoby, Joseph Jacob:
Learning Morphological Feature Perturbations for Calibrated Semi-Supervised Segmentation. 1413-1429 - Yanwu Yang, Xutao Guo, Chenfei Ye, Yang Xiang, Ting Ma:
Regularizing Brain Age Prediction via Gated Knowledge Distillation. 1430-1443 - Yuan Yao, Fengze Liu, Zongwei Zhou, Yan Wang, Wei Shen, Alan L. Yuille, Yongyi Lu:
Unsupervised Domain Adaptation through Shape Modeling for Medical Image Segmentation. 1444-1458 - Anna Yeaton, Rahul G. Krishnan, Rebecca J. Mieloszyk, David Alvarez-Melis, Grace Huynh:
Hierarchical Optimal Transport for Comparing Histopathology Datasets. 1459-1469 - Sixing Yin, Yameng Han, Judong Pan, Yining Wang, Shufang Li:
Left Ventricle Contouring in Cardiac Images Based on Deep Reinforcement Learning. 1470-1481 - Evan M. Yu, Alan Q. Wang, Adrian V. Dalca, Mert R. Sabuncu:
KeyMorph: Robust Multi-modal Affine Registration via Unsupervised Keypoint Detection. 1482-1503 - Weicheng Zhu, Carlos Fernandez-Granda, Narges Razavian:
Interpretable Prediction of Lung Squamous Cell Carcinoma Recurrence With Self-supervised Learning. 1504-1522 - Xiner Zhu, Haoji Hu, Hualiang Wang, Jincao Yao, Wei Li, Di Ou, Dong Xu:
Region Aware Transformer for Automatic Breast Ultrasound Tumor Segmentation. 1523-1537
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 2024-12-29 20:18 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: