Shifeng Tian1, Ailian Liu1, Yan Guo2, and Yuan Wei1
1Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China, China, 2GE Healthcare, Dalian City, China, China
1Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China, China, 2GE Healthcare, Dalian City, China, China
A total of 386 imaging features were extracted, and 7 omics characteristics related to cervical cancer pathological classification were obtained by dimension reduction.
Figure 1:A 56 year old patient with cervical mucinous adenocarcinoma.1A shows T2WI image and the red arrow points to cervical cancer;1B shows the MK pseudo color map of DKI sequence of corresponding layer; 1C shows the ROI outline of corresponding layer, and the red area shows the coverage area of tumor parenchyma.