Jerome Zhengrong Liang1, Lihong Li2, Chaijie Duan1, Su Wang1, Mark Wagshul1, Hongbing Lu3
1Radiology, Stony Brook University, Stony Brook, NY, USA; 2Dept. of Engineering Science and Physics, The City University of New York, Staten Island, NY, USA; 3Biomedical Engineering, Fourth Military Medical University, Xian, Shannxi, China
Bladder cancer is the fifth leading cause of cancer-related deaths in the US and is difficult to manage because of the high recurrence rate after resection of the tumors (as high as 80%). It is essential to detect bladder abnormalities in a non-invasive and convenience manner, especially for follow-ups on resection. This paper presents a MRI-virtual cystoscopy system, which extracts the bladder wall from T1 images where the wall is enhanced while the urine and surrounding fat are suppressed. It analyzes the extracted wall and detects abnormal features automatically. Test results are encouraging by FROC merit.