Spring 2025 www.pigchamp.com 9 The Anatomic Atlas At Topigs Norsvin, the CT scanning process consists of collecting whole-body, 3D images for each pig. CT images are collected at market weight (approximately 286 lbs.) for all purebred boars at the Delta Canada and Delta Norway boar off-testing stations. The first step in this process is sedation—sedating the pig enables technicians to load and position boars on the CT table as safely as possible. During the scanning process, thousands of images are captured per individual. These images contain pixels. While a given pixel may contain information on multiple tissue types, these tissues can be distinguished using AI models. This same process was used to develop what we refer to as an AI-based anatomical “atlas.” This provides an overview of the positioning and size of each anatomical structure within a CT image. Using this atlas, the tissue of any CT image can be segmented into 29 different classes, including muscle, organ, and bone tissue (Figure 2). Within the bone tissue, more specific algorithms are systematically used to identify joints connecting bones and any detectable instances of osteochondrosis lesions within these joints. Joint Identification Each major leg bone has two extreme points, which are located at the end of the bone. The center of a joint is identified based on the position of these extreme points of two neighboring bones. Bounding boxes (Figure 3) are then constructed around the center point of each joint to define the region of interest for the identification of osteochondrosis lesions. For example, bounding boxes improve the lesion-to-background ratio from approximately 1:1,000,000 to 1:10,000, reducing the computational complexity of segmentation in this region. Looking at the Automated Segmentation of Osteochondrosis Lesions In 2015, groundbreaking AI models were introduced for the segmentation of medical images (RonnerAutomated segmentation of a whole-body CT image into 29 distinct tissue types, including bone, muscle, and organ tissue. Figure 3 Automated detection of the humerus (yellow), tibia and fibula (blue), extreme points (pink circles), and bounding box surrounding the stifle joint (pink cube). Figure 2
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