Three-dimensional vessel segmentation in whole-tissue and whole-block imaging using a deep neural network: Proof of concept study

In the field of pathology, micro computed tomography (micro-CT) has become attractive imaging modality because it enables full analysis of the three-dimensional (3D) characteristics of a tissue sample or organ in a non-invasive manner. However, due to the complexity of the 3D information, understanding would be improved by development of analytical methods and software such as those implemented for clinical CT. As the accurate identification of tissue components is critical for this purpose, we have developed a deep neural network (DNN) to analyze whole-tissue images (WTI) and whole-block images (WBI) of neoplastic cancer tissue using micro-CT.

Source: American Journal of Pathology - December 23, 2020 Category: Pathology Authors: Takashi Ohnishi, Alexei Teplov, Noboru Kawata, Kareem Ibrahim, Peter Ntiamoah, Canan Firat, Hideaki Haneishi, Meera Hameed, Jinru Shia, Yukako Yagi Source Type: research