A computer aided diagnostic system for radiotherapy planning.
Planning for radiation therapy intervention implies the definition of treatment volumes as well as a clear delimitation of normal tissue. This paper presents a Computer Aided Diagnostic system for the automatic CT image analysis. Two important problems are solved: the spinal cord segmentation and the detection of lung metastases. Some subordinate problems are also solved: the detection of spinal canal, lamina, lungs, and ribs, as well as the identification of thorax contour. The developed methodologies use a knowledge-driven image processing based on Anatomical Structures Maps and task-oriented architecture. Experiments were performed on CT images from La Chaux de Fonds Hospital (Switzerland). Evaluations were performed using a visual inspection of the contours projected on the CT image slices. The radiologist decided whether each of the contours obtained with our system was acceptable or not. The accuracy of the method was defined as the fraction of CT slices in which the particular contour was correctly located. In the case of spinal cord segmentation, the procedure was tested on 23 patients (1051 images), resulting in an accuracy of 91%. In the case of lung tumors detection, the method showed an accuracy of > 90%, with testing performed on 20 patients for a total of 988 images. The experiments performed show that the method is reliable, with possible future application in an oncology department.
Archip
Neculai
N
Electrical and Computer Engineering Department, University of British Columbia, Canada. Neculai.Archip@ccc.ubc.ca
Erard
Pierre-Jean
PJ
Haefliger
Jean-Marie
JM
Germond
Jean-François
JF
D006801:Humans; D007091:Image Processing, Computer-Assisted; D019047:Phantoms, Imaging; D011880:Radiotherapy Planning, Computer-Assisted; D013116:Spinal Cord / Q000033:anatomy & histology; D014057:Tomography, X-Ray Computed