Landmarking of computed tomographic images to assist in segmentation of abdominal tumors caused by neuroblastoma.
Segmentation of the primary tumor mass in neuroblastoma could aid radiologists by facilitating reproducible and objective quantification of the tumor's tissue composition and size. However, due to the heterogeneous nature of the tissue components of the neuroblastic tumor, ranging from low-attenuation necrosis to high-attenuation calcification, some of which possess strong similarities with adjacent nontumoral tissues in computed tomographic (CT) images, segmentation of the tumor is a difficult problem. In this context, landmarking methods are proposed to assist in the segmentation of neuroblastic tumors. Methods are proposed to identify and segment automatically the rib structure, the vertebral column, the spinal canal, the diaphragm, and the pelvic girdle. The use of the landmarks assisted in limiting the scope of the tumor segmentation process to the abdomen, and resulted in the reduction of the false-positive error rates by 26.9%, on the average, over 10 CT exams, and improved the result of segmentation of neuroblastic tumors.
Banik
Shantanu
S
Department of Electrical and Computer Engineering, Schulich School of Engineering, University of Calgary, Alberta, Canada.
Rangayyan
Rangaraj M
RM
Boag
Graham S
GS
D000005:Abdomen / Q000473:pathology; D000008:Abdominal Neoplasms / Q000473:pathology* / Q000556:secondary*; D000293:Adolescent; D000328:Adult; D001932:Brain Neoplasms / Q000473:pathology*; D002648:Child; D002675:Child, Preschool; D003936:Diagnosis, Computer-Assisted; D005189:False Positive Reactions; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D016018:Least-Squares Analysis; D009447:Neuroblastoma / Q000473:pathology*; D011857:Radiographic Image Interpretation, Computer-Assisted; D015203:Reproducibility of Results; D014057:Tomography, X-Ray Computed / Q000379:methods*