VinDr-Multiphase: A Benchmark Dataset for Phase Recognition in Abdominal Contrast-Enhanced CT Scans

Dataset Description

This dataset was used to develop and validate our proposed method for phase recognition in abdominal contrast-enhanced CT scans using deep learning and random sampling.

Figure 1: Visual differences between the Non-Contrast (NC), Arterial (A), and Venous (V) phases in CT scans. The radiation enhancement in the different phases helps to detect different lesions in CT scans such as metastases, central tumor necrosis, and other pathologies. Radiologists usually look at arteries or veins and parenchyma to distinguish the phases.

Table 1. Characteristics of patients in the training and test datasets.


To download the VinDr-Multiphase dataset, please sign our Data Use Agreement (DUA) and send the signed DUA to v.md@vinbigdata.org for obtaining the downloadable link.


For any publication that explores this resource, the authors must cite this original paper:

Binh T. Dao, Thang V. Nguyen, Hieu H. Pham, and Ha Q. Nguyen, “Phase Recognition in Contrast-Enhanced CT Scans based on Deep Learning and Random Sampling,” Medical Physics, to appear.


Correspondence should be addressed to v.md@vinbigdata.org.