Computer vision, pattern recognition and image processing in left ventricle segmentation: The last 50 years
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 surveys state-of-the-are computer vision and pattern recognition techniques for Left Ventricle (LV) segmentation and modelling juring the second half of the twentieth century The paper presents the key characteristics of successful model-based segmentation techniques for LV modelling. This sun ey paper concludes the following: (1) any one pattern recognition or computer vision technique is nut sufficient for accurate 2D, 3D or 4D modelling of LV; (2) fitting mathematical models for LV modelling have dominated in the last 15 years; (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 bern paid to LV modelling validation.
computer vision pattern recognition left ventricle model-based boundaries learning quantification tracking wall motion