Abstract
Computed Tomographic Colonography (CTC) is a minimally invasive method that allows the examination of the colon wall from the source CT sections or in a virtual environment. The primary goal of CTC is the detection of colonic polyps. There are typically two data sets recorded in supine and prone positions. An important step in polyp detection is the anatomical registration of these datasets. We developed and experimentally validated a method to register complementary supine and prone CTC datasets anatomically, using linear stretching/shrinking operations on the medial axis colonic path based on the relative path geometries. To compare improvement in spatial registration of supine and prone datasets, a radiologist determined 5 unique reference points (RP) in the registered and unregistered datasets from each of 5 patients by viewing supine and prone data simultaneously. Initial results suggest that our algorithm is capable of registering supine and prone CTC data anatomically within an approximate range of ±13.2mm, which corresponds to 0.8% error with respect to the average colon length.
Original language | English (US) |
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Pages (from-to) | 2433-2436 |
Number of pages | 4 |
Journal | Annual Reports of the Research Reactor Institute, Kyoto University |
Volume | 3 |
State | Published - Dec 1 2001 |
Externally published | Yes |
Event | 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Istanbul, Turkey Duration: Oct 25 2001 → Oct 28 2001 |
Keywords
- Anatomical data registration
- CTC
- Data fusion
- Registering prone and supine data for CTC
- Virtual colonography
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Mechanical Engineering