Did You Get What You Paid For? Rethinking Annotation Cost of Deep Learning Based Computer Aided Detection in Chest Radiographs

30 September 2022

Papers citing "Did You Get What You Paid For? Rethinking Annotation Cost of Deep Learning Based Computer Aided Detection in Chest Radiographs"

7 / 7 papers shown

Title
Augmenting Chest X-ray Datasets with Non-Expert Annotations Veronika Cheplygina Cathrine Damgaard Dovile Juodelyte Veronika Cheplygina Amelia Jiménez-Sánchez 101 4 0 05 Sep 2023
Deep Learning for Chest X-ray Analysis: A Survey Ecem Sogancioglu E. Çallı Bram van Ginneken K. G. V. Leeuwen K. Murphy LM&MA 89 324 0 15 Mar 2021
CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT Akshay Smit Saahil Jain Pranav Rajpurkar Anuj Pareek A. Ng M. Lungren MedIm 39 331 0 20 Apr 2020
Deep learning with noisy labels: exploring techniques and remedies in medical image analysis Davood Karimi Haoran Dou Simon K. Warfield Ali Gholipour NoLa 88 541 0 05 Dec 2019
Exploring large scale public medical image datasets Luke Oakden-Rayner 55 174 0 30 Jul 2019
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison Jeremy Irvin Pranav Rajpurkar M. Ko Yifan Yu Silviana Ciurea-Ilcus ... D. Larson C. Langlotz Bhavik Patel M. Lungren A. Ng 110 2,591 0 21 Jan 2019
Generalised Dice overlap as a deep learning loss function for highly unbalanced segmentations Carole H Sudre Wenqi Li Tom Vercauteren Sébastien Ourselin M. Jorge Cardoso SSeg 117 2,146 0 11 Jul 2017