Computer Vision, Pattern Recognition and Image Processing in Left Ventricle Segmentation: The Last 50 Years

Abstract

In the last decade, computer vision, pattern recognition, image processing and cardiac researchers have given immense attention to cardiac image analysis and modelling. This paper survets state-of-the-art computer vision and pattern recognition techniques for Left Ventricle (LV) segmentation and modelling during the second half of the twentieth century. The paper presents the key charateristics of successful model-based segmentation and modelling during the second half of the twentieth century. The paper presents the key characteristics of successful model-based segmentation techniques for LV modelling. This survey paper concludes the following: (1) any one pattern recognition or computer vision technique is not sufficient for accurate 2D, 3D or 4D modelling of LV; (2) fitting mathematical models for LV modelling have dominated in the last 15 tears; (3) knowledge extrated from the ground truth has lead to very successful attempts for LV modelling have dominated in the last 15 uears; (3) knowledge extracted from the ground truth has lead to very successful attempts at LV modelling;(4) spatial and temporal behaviour of LV through different imaging modalities has yielded information which has led to accurate LV modelling; and (5) not much attention has been paid to LC modelling validation.