36 datasets found

The dataset contains organ-level vision-text pairs from 17,702 patients across 104 organs.

Medical Vision-Language Pretraining (Med-VLP) establishes a connection between visual content from medical images and the relevant textual descriptions. Existing Med-VLP methods...

Extraction of airways from CT (EXACT’09).

A dataset for vertebrae detection and localization in CT scans

The Internal Multi-Organ (IMO) dataset contains 85 CT-scans annotated with 7 classes.

The TCIA pancreas public dataset contains 82 CT-scans with pixel-level annotations.

The NIH dataset contains 14 different diseases, including pneumonia, and is used for training and testing machine learning models.

The Total Segmentator dataset contains 1204 CT images with labels of 104 anatomical structures.

The NIH-Lymph Node (NIH-LN) dataset includes 176 chest-abdomen-pelvis CT scans.

The AUTOMI CT dataset, consisting of full-body CT scans from the Humanitas Research Hospital in Milan.

The dataset used in this work, consisting of CT scans of the abdominal region from the CHAOS challenge, and MRI scans of the same region from the CHAOS challenge.

A dataset of 70 tampered and 30 authentic CT scans for evaluation of CT-GAN attack

A dataset of 888 CT scans collected in the LIDC-IDRI lung cancer screening trial

The A Lung Nodule Database (LNDb) dataset is used for training and testing a ResNet-50 model to classify CT scans of lungs acquired with or without contrast agents.

The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) dataset is used for training and testing a ResNet-50 model to classify CT scans of lungs...

LIDC-IDRI dataset contains almost all the related information for low-dose lung CTs including several doctors' annotations on nodule sizes, locations, diagnosis results, nodule...