MIDL 2021

59 papers

Hybrid optimization between iterative and network fine-tuning reconstructions for fast quantitative susceptibility mapping

Jinwei Zhang, Hang Zhang, Pascal Spincemaille, Thanh Nguyen, Mert R. Sabuncu

SWNet: Surgical Workflow Recognition with Deep Convolutional Network

Bokai Zhang, Amer Ghanem, Alexander Simes, Henry Choi, Andrew Yoo

A regularization term for slide correlation reduction in whole slide image analysis with deep learning

Hongrun Zhang, Yanda Meng, Xuesheng Qian, Xiaoyun Yang, Sarah E. Coupland

Automated triaging of head MRI examinations using convolutional neural networks

David A. Wood, Sina Kafiabadi, Aisha Al Busaidi, Emily Guilhem, Antanas Montvila

Untangling the Small Intestine in 3D cine-MRI using Deep Stochastic Tracking

Louis van Harten, Catharina de Jonge, Jaap Stoker, Ivana Isgum

HAD-Net: A Hierarchical Adversarial Knowledge Distillation Network for Improved Enhanced Tumour Segmentation Without Post-Contrast Images

Saverio Vadacchino, Raghav Mehta, Nazanin Mohammadi Sepahvand, Brennan Nichyporuk, James J. Clark

Guided Filter Regularization for Improved Disentanglement of Shape and Appearance in Diffeomorphic Autoencoders

Hristina Uzunova, Heinz Handels, Jan Ehrhardt

Learning the Latent Heat Diffusion Process through Structural Brain Network from Longitudinal β-Amyloid Data

Md Asadullah Turja, Guorong Wu, Defu Yang, Martin Andreas Styner

A Mean-Field Variational Inference Approach to Deep Image Prior for Inverse Problems in Medical Imaging

Malte Tölle, Max-Heinrich Laves, Alexander Schlaefer

MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models

Hari Sowrirajan, Jingbo Yang, Andrew Y. Ng, Pranav Rajpurkar

Changing the Contrast of Magnetic Resonance Imaging Signals using Deep Learning

Attila Tibor Simko, Tommy Löfstedt, Anders Garpebring, Mikael Bylund, Tufve Nyholm

Unseen Disease Detection for Deep Learning Interpretation of Chest X-rays

Siyu Shi, Ishaan Malhi, Kevin Tran, Andrew Y. Ng, Pranav Rajpurkar

Cluster-to-Conquer: A Framework for End-to-End Multi-Instance Learning for Whole Slide Image Classification

Yash Sharma, Aman Shrivastava, Lubaina Ehsan, Christopher A. Moskaluk, Sana Syed

Understanding and Visualizing Generalization in UNets

Abhejit Rajagopal, Vamshi Chowdary Madala, Thomas A Hope, Peder Larson

Learning Diffeomorphic and Modality-invariant Registration using B-splines

Huaqi Qiu, Chen Qin, Andreas Schuh, Kerstin Hammernik, Daniel Rueckert

Image Sequence Generation and Analysis via GRU and Attention for Trachomatous Trichiasis Classification

Juan Carlos Prieto, Hina Shah, Kasey Jones, Robert F Chew, Hashiya M. Kana

Residual learning for 3D motion corrected quantitative MRI: Robust clinical T1, T2 and proton density mapping

Carolin Pirkl, Matteo Cencini, Jan W. Kurzawski, Diana Waldmannstetter, Hongwei Li

Unsupervised Brain Anomaly Detection and Segmentation with Transformers

Walter Hugo Lopez Pinaya, Petru-Daniel Tudosiu, Robert Gray, Geraint Rees, Parashkev Nachev

Localizing Neurosurgical Instruments Across Domains and in the Wild

Markus Philipp, Anna Alperovich, Marielena Gutt-Will, Andrea Mathis, Stefan Saur

Explainable Image Quality Analysis of Chest X-Rays

Caner Ozer, Ilkay Oksuz

Balanced sampling for an object detection problem - application to fetal anatomies detection

Antoine Olivier, Caroline Raynaud

GOAL: Gist-set Online Active Learning for Efficient Chest X-ray Image Annotation

Chanh Nguyen, Minh Thanh Huynh, Minh Quan Tran, Ngoc Hoang Nguyen, Mudit Jain

“Train one, Classify one, Teach one” - Cross-surgery transfer learning for surgical step recognition

Daniel Neimark, Omri Bar, Maya Zohar, Gregory D. Hager, Dotan Asselmann

EPIC-Survival: End-to-end Part Inferred Clustering for Survival Analysis, with Prognostic Stratification Boosting

Hassan Muhammad, Chensu Xie, Carlie S Sigel, Michael Doukas, Lindsay Alpert

Learning Interclass Relations for Intravenous Contrast Phase Classification in CT

Raouf Muhamedrahimov, Amir Bar, Ayelet Akselrod-Ballin

Unifying Brain Age Prediction and Age-Conditioned Template Generation with a Deterministic Autoencoder

Pauline Mouches, Matthias Wilms, Deepthi Rajashekar, Sonke Langner, Nils Forkert

An AI-based Framework for Diagnostic Quality Assessment of Ankle Radiographs

Dominik Mairhöfer, Manuel Laufer, Paul Martin Simon, Malte Sieren, Arpad Bischof

Distill DSM: Computationally efficient method for segmentation of medical imaging volumes

Harsh Maheshwari, Vidit Goel, Ramanathan Sethuraman, Debdoot Sheet

Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosis

Kangning Liu, Yiqiu Shen, Nan Wu, Jakub Piotr Chłędowski, Carlos Fernandez-Granda

Improved model-based deep learning for quantitative susceptibility mapping

Juan Liu

Benefits of Linear Conditioning for Segmentation using Metadata

Andréanne Lemay, Charley Gros, Olivier Vincent, Yaou Liu, Joseph Paul Cohen

Embedding-based Instance Segmentation in Microscopy

Manan Lalit, Pavel Tomancak, Florian Jug

Predicting COVID-19 Lung Infiltrate Progression on Chest Radiographs Using Spatio-temporal LSTM based Encoder-Decoder Network

Aishik Konwer, Joseph Bae, Gagandeep Singh, Rishabh Gattu, Syed Ali

Feature-based image registration in structured light endoscopy

Andreas M Kist, Julian Zilker, Michael Döllinger, Marion Semmler

Beyond pixel-wise supervision for segmentation: A few global shape descriptors might be surprisingly good!

Hoel Kervadec, Houda Bahig, Laurent Letourneau-Guillon, Jose Dolz, Ismail Ben Ayed

Partial transfusion: on the expressive influence of trainable batch norm parameters for transfer learning

Fahdi Kanavati, Masayuki Tsuneki

Feedback Graph Attention Convolutional Network for MR Images Enhancement by Exploring Self-Similarity Features

Xiaobin Hu, Yanyang Yan, Wenqi Ren, Hongwei Li, Amirhossein Bayat

Whole-Body Soft-Tissue Lesion Tracking and Segmentation in Longitudinal CT Imaging Studies

Alessa Hering, Felix Peisen, Teresa Amaral, Sergios Gatidis, Thomas Eigentler

CNN and Deep Sets for End-to-End Whole Slide Image Representation Learning

Sobhan Hemati, Shivam Kalra, Cameron Meaney, Morteza Babaie, Ali Ghodsi

The OOD Blind Spot of Unsupervised Anomaly Detection

Matthäus Heer, Janis Postels, Xiaoran Chen, Ender Konukoglu, Shadi Albarqouni

Weakly Supervised Volumetric Segmentation via Self-taught Shape Denoising Model

Qian He, Shuailin Li, Xuming He

Discrete Pseudohealthy Synthesis: Aortic Root Shape Typification and Type Classification with Pathological Prior

Jannis Hagenah, Floris Ernst

Membership Inference Attacks on Deep Regression Models for Neuroimaging

Umang Gupta, Dimitris Stripelis, Pradeep K. Lam, Paul Thompson, José Luis Ambite

Direct Inference of Cell Positions using Lens-Free Microscopy and Deep Learning

Philipp Gruening, Falk Nette, Noah Heldt, Ana Cristina Guerra de Souza, Erhardt Barth

Self-supervised Out-of-distribution Detection for Cardiac CMR Segmentation

Camila Gonzalez, Anirban Mukhopadhyay

CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray Segmentation

Soham Uday Gadgil, Mark Endo, Emily Wen, Andrew Y. Ng, Pranav Rajpurkar

Nuc2Vec: Learning Representations of Nuclei in Histopathology Images with Contrastive Loss

Chao Feng, Chad Vanderbilt, Thomas Fuchs

Tailoring automated data augmentation to H&E-stained histopathology

Khrystyna Faryna, Jeroen van der Laak, Geert Litjens

A Surprisingly Effective Perimeter-based Loss for Medical Image Segmentation

Rosana EL Jurdi, Caroline Petitjean, Paul Honeine, Veronika Cheplygina, Fahed Abdallah

Intensity Correction and Standardization for Electron Microscopy Data

Oleh Dzyubachyk, Roman I Koning, Aat A Mulder, M. Christina Avramut, Frank GA Faas

Improving MRI-based Knee Disorder Diagnosis with Pyramidal Feature Details

Matteo Dunnhofer, Niki Martinel, Christian Micheloni

M-GCN: A Multimodal Graph Convolutional Network to Integrate Functional and Structural Connectomics Data to Predict Multidimensional Phenotypic Characterizations

Niharika Shimona Dsouza, Mary Beth Nebel, Deana Crocetti, Joshua Robinson, Stewart Mostofsky

Steffen Czolbe, Oswin Krause, Aasa Feragen

Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Counterfactual Generation for Chest X-rays

Joseph Paul Cohen, Rupert Brooks, Sovann En, Evan Zucker, Anuj Pareek

Improving Weakly Supervised Lesion Segmentation using Multi-Task Learning

Tianshu Chu, Xinmeng Li, Huy V. Vo, Ronald M. Summers, Elena Sizikova

An MRF-UNet Product of Experts for Image Segmentation

Mikael Brudfors, Yael Balbastre, John Ashburner, Geraint Rees, Parashkev Nachev

Attention via Scattering Transforms for Segmentation of Small Intravascular Ultrasound Data Sets

Lennart Bargsten, Katharina A. Riedl, Tobias Wissel, Fabian J. Brunner, Klaus Schaefers

Stroke Lesion Outcome Prediction Based on 4D CT Perfusion Data Using Temporal Convolutional Networks

Kimberly Amador, Matthias Wilms, Anthony Winder, Jens Fiehler, Nils Forkert

Self-Rule to Adapt: Learning Generalized Features from Sparsely-Labeled Data Using Unsupervised Domain Adaptation for Colorectal Cancer Tissue Phenotyping

Christian Abbet, Linda Studer, Andreas Fischer, Heather Dawson, Inti Zlobec