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This paper presents a colonoscope tracking method utilizing a colon shapeestimation method. CT colonography is used as a less-invasive colon diagnosismethod. If colonic polyps or early-stage cancers are found, they are removed ina colonoscopic examination. In the colonoscopic examination, understandingwhere the colonoscope running in the colon is difficult. A colonoscopenavigation system is necessary to reduce overlooking of polyps. We propose acolonoscope tracking method for navigation systems. Previous colonoscopetracking methods caused large tracking errors because they do not considerdeformations of the colon during colonoscope insertions. We utilize the shapeestimation network (SEN), which estimates deformed colon shape duringcolonoscope insertions. The SEN is a neural network containing long short-termmemory (LSTM) layer. To perform colon shape estimation suitable to the realclinical situation, we trained the SEN using data obtained during colonoscopeoperations of physicians. The proposed tracking method performs mapping of thecolonoscope tip position to a position in the colon using estimation results ofthe SEN. We evaluated the proposed method in a phantom study. We confirmed thattracking errors of the proposed method was enough small to perform navigationin the ascending, transverse, and descending colons.

Colonoscope tracking method based on shape estimation network