You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: A Review on the Extraction of Quantitative Retinal Microvascular Image Feature 
Chapter Title:  Zero Crossing Edge Detector, and Canny Edge Detector (Gonzalez, Woods, & Eddins, 2009). 
1. Abstract of Cited Paper (BIB001):  Optic disc (OD) detection is an important step in developing systems for automated diagnosis of various serious ophthalmic pathologies. This paper presents a new template-based methodology for segmenting the OD from digital retinal images. This methodology uses morphological and edge detection techniques followed by the Circular Hough Transform to obtain a circular OD boundary approximation. It requires a pixel located within the OD as initial information. For this purpose, a location methodology based on a voting-type algorithm is also proposed. The algorithms were evaluated on the 1200 images of the publicly available MESSIDOR database. The location procedure succeeded in 99% of cases, taking an average computational time of 1.67 s. with a standard deviation of 0.14 s. On the other hand, the segmentation algorithm rendered an average common area overlapping between automated segmentations and true OD regions of 86%. The average computational time was 5.69 s with a standard deviation of 0.54 s. Moreover, a discussion on advantages and disadvantages of the models more generally used for OD segmentation is also presented in this paper.

Literature Review:
Edge detection is an important way to extract the key features of retinal microvasculature. A variety of edge detecting algorithms are being developed in fundus retinal image processing. The authors of BIB001 developed a fundus coordinate system combining region growing and edge detection to detect the exudates, an important feature of the retinal image, and modified active shape model to detect the disc boundary of fundus retinal image. The success rate of their algorithm in terms of detecting optic disc boundary is 94% and the sensitivity and specificity of detecting exudates are 100% and 71%, respectively BIB001 . A template-based retinal image segmentation was presented in BIB002 in which morphological and edge detection technique employing the circular Hough transform for approximating the circular optic disc boundary was applied.