Multitemporal liver analysis for surgical plan and clinical follow-up, adapted for Sibgrapi 2019

The Computed tomography (CT) images have been widely used in diagnosis of diseases, for surgical planning and transplantation. Not only targeting the relevant structures but also as the automatic volume measurement based on segmentation are a critical step for computer-aided diagnosis and surgical planning (POHLE, 2003) (F, 2002). In particular, the analysis of liver imaging obtained by CT presents some challenges. This organ presents a topographic anatomy different from the functional anatomy. This was described by Claude Couinaud (COUINAUD C.; DELMAS, 1957), from the anatomical studies that detailed the 8 functional units of the liver, known as hepatic segments.Currently the conditions of analysis of computerized tomography’s are basically visual, performing them from 2D images (R, 1999). According to (F, 2002) this ends up being a source of errors, since the expert is subjected to an exhaustive routine of analysis from avery large number of images, and the fatigue can cause errors of interpretation by human failure. In order to aid in surgical planning and clinical follow - up, an application was developed that transforms the computational tomography, previously into 2D images, into a 3D model that can be used in the web application developed in this work allowing a multitemporal analysis of the liver.