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Esophageal Gross Tumor Volume Segmentation using a 3D Convolutional Neural Ne...
Esophageal gross tumor volume segmentation using a 3D convolutional neural network -
Esophageal GTV Segmentation using a 3D Convolutional Neural Network
Esophageal GTV segmentation using a 3D convolutional neural network -
Prostate158-An expert-annotated 3T MRI dataset and algorithm for prostate can...
A 3T MRI dataset and algorithm for prostate cancer detection. -
Automatic detection and diagnosis of sacroiliitis in CT scans as incidental f...
A new automatic algorithm for the diagnosis and grading of sacroiliitis in CT scans as incidental findings, for patients who underwent lower back or abdomen CT scanning as part... -
Chest X-ray Dataset
The dataset used in this study comprises X-ray images representing pneumonia cases and those depicting normal conditions. -
Robustification of Segmentation Models Against Adversarial Perturbations In Me...
A defense framework for segmentation models against adversarial attacks in medical imaging -
Head and Neck FDG PET-CT TCIA Dataset
A dataset used for outcome prediction in head and neck cancer -
Head-Neck-PET-CT
A public TCIA head and neck cancer dataset used for outcome prediction -
3D Stent and Marker Dataset
A dataset of 3D stents and 3D customized markers for training and testing the 3D shape instantiation framework. -
Real-time 3D Shape Instantiation for Partially-deployed Stent Segment
A 3D shape instantiation framework for partially-deployed stent segment from a single intra-operative 2D fluoroscopic image. -
Radiopaedia COVID-19 Lung Infections in Chest CT volumes
The dataset used in this work consists of 9 axial volumes from Radiopaedia consisting of both positive and negative COVID indications. -
Jun et al. COVID-19 Lung Infections in Chest CT volumes
The dataset used in this work consists of 20 volumes from Jun et al. consisting of infections labelled by two radiologists and verified by another experienced radiologist. -
COVID-19 Lung Infections in Chest CT volumes
The dataset used in this work consists of 29 CT volumes from two different sources of lung infection data, resulting from COVID-19. -
TCIA, 5-patients, and ELCAP public dataset
A dataset was prepared with the help of experienced medical experts. The dataset was used to train the UNet model. -
Generative enhancement for 3d medical images
Generative enhancement for 3d medical images -
Deep Learning Framework for Spatiotemporal Ultrasound Localization Microscopy
Ultrasound Localization Microscopy can resolve the microvascular bed down to a few micrometers. To achieve such performance microbubble contrast agents must perfuse the entire... -
Multi-view analysis of unregistered medical images using cross-view transformers
Multi-view analysis of unregistered medical images using cross-view transformers. -
TCGA-NSCLC
The TCGA-NSCLC dataset includes two sub-types of lung cancer, Lung Adenocarcinoma (LUAD) and Lung Squamous Cell Carcinoma (LUSC). -
MIMIC-CXR-JPG
MIMIC-CXR-JPG dataset comprises 227,835 imaging studies conducted on 64,588 patients who sought treatment at the BIDMC Emergency Department from 2011 to 2016.