  This paper presents a colonoscope tracking method utilizing a colon shape
estimation method. CT colonography is used as a less-invasive colon diagnosis
method. If colonic polyps or early-stage cancers are found, they are removed in
a colonoscopic examination. In the colonoscopic examination, understanding
where the colonoscope running in the colon is difficult. A colonoscope
navigation system is necessary to reduce overlooking of polyps. We propose a
colonoscope tracking method for navigation systems. Previous colonoscope
tracking methods caused large tracking errors because they do not consider
deformations of the colon during colonoscope insertions. We utilize the shape
estimation network (SEN), which estimates deformed colon shape during
colonoscope insertions. The SEN is a neural network containing long short-term
memory (LSTM) layer. To perform colon shape estimation suitable to the real
clinical situation, we trained the SEN using data obtained during colonoscope
operations of physicians. The proposed tracking method performs mapping of the
colonoscope tip position to a position in the colon using estimation results of
the SEN. We evaluated the proposed method in a phantom study. We confirmed that
tracking errors of the proposed method was enough small to perform navigation
in the ascending, transverse, and descending colons.
