An insightful and thorough manual on the automated identification and classification of diabetic eye disorders using digital fundus photos can be found in Kevin Prathap Noronha's "Automated Identification of Diabetic Eye Diseases Using Digital Fundus Images." Medical experts, researchers, and students who are interested in creating intelligent systems for the early diagnosis of diabetic retinopathy and other eye conditions should read this book.

The author gives a thorough explanation of diabetic retinopathy and the difficulties in identifying it early. The methodologies for digital fundus image processing, segmentation algorithms, and feature extraction methods necessary for correctly diagnosing diabetic eye disorders are all covered in-depth in this book.

Noronha also discusses the automated detection and categorization of diabetic eye disorders using machine learning approaches including artificial neural networks, support vector machines, and decision trees. The book offers readers step-by-step instructions for using these strategies while utilising the most recent open-source software tools and frameworks.

All things considered, "Automated Identification of Diabetic Eye Diseases Using Digital Fundus Images" is a crucial tool for anyone working to create intelligent systems for the early recognition of diabetic eye diseases. Both professionals and students alike should study it since it makes a significant addition to the field of medical image processing.

In conclusion, this book is a fantastic resource for researchers, professionals, and students who are interested in creating automated methods for exploiting digital fundus images to detect diabetic eye problems early.