Application and Systematization of CA
Computational anatomy (CA) has the potential to change the world of medical imaging techniques. Its detailed analysis of anatomy holds the promise of improved quality and precision of diagnostic imaging and therapy.
Well-designed CA-assisted medical imaging and surgical systems are beginning to play a role in many centers. These systems are mainly classified into three categories: (a) computer-aided diagnosis (CAD), (b) surgical assistance systems, and (c) fusion-aid system of diagnosis and surgery.
CA aims to systematize whole-body anatomy based on medical images with the aim of providing supporting technologies for medical image interpretation and surgery. For example, in automated detection of lymph nodes from computed tomographic (CT) images, anatomical structure information may reduce falsepositive regions from candidate sets of lymph nodes. The Hessian-based approach for lymph node extraction from volumetric CT images detects many false-positive foci in regions such as the small or large intestine. Such false-positive regions can be easily removed if we could understand patient anatomy from CT images.
Another example is utilization of patient anatomy data from medical images in computer-assisted intervention. Surgical navigation assistance is used widely for efficiency and achieving optimal outcomes. A typical surgical navigation system can show the location of a forceps in real time on three-dimensional (3D) rendered views of a surgical patient. A surgical navigation system provides 3D rendering of
Division of Radiology, Department of Radiology and Laboratory Medicine, Faculty of Medical Sciences, University of Fukui, 23-3 Matsuoka-Shimoaizuki, Eiheiji, Fukui 910-1193, Fukui, Japan