Statistical shape modeling of multi-organ anatomies with shared boundaries

• DOI: 10.3389/fbioe.2022.1078800
• Publication Date: 2023-01-12T04:26:37Z
• Authors: Krithika Iyer; Alan Morris; Brian Zenger; Karthik Karanth; Nawazish Khan; Benjamin A. Orkild; Oleksandre Korshak; Shireen Elhabian
• Keywords: Representation; Position (finance)

Statistical shape modeling (SSM) is a valuable and powerful tool to generate detailed representation of complex anatomy that enables quantitative analysis shapes their variations. SSM applies mathematics, statistics, computing parse the into some (such as correspondence points or landmarks) which can be used study covariance patterns answer various questions about anatomical variations across population. Complex structures have many diverse parts with varying interactions intricate architecture. For example, heart four-chambered organ several shared boundaries between chambers. Subtle changes within indicate potential pathologic such right ventricular overload. Early detection robust quantification could provide insight ideal treatment techniques intervention timing. However, existing methods do not explicitly handle aid in better understanding interest. If are modeled, it restricts capability model identify pathological occurring at boundary. Hence, this paper presents general flexible data-driven approach for building statistical models multi-organ anatomies contact surfaces.