Book Automated Diagnosis Of Glaucoma Using Ai Techniques: Neural Networks, Decision Trees, Naïve Bayes, And Support Vector Machine Pdf Epub Ebook ISBN-10 384542821X, ISBN-13 978-3845428

Automated Diagnosis Of Glaucoma Using Ai Techniques: Neural Networks, Decision Trees, Naïve Bayes, And Support Vector Machine

By autor: Ahmed Salah Ghorab
DMCA

Glaucoma is a major cause of blindness globally. It damages the optic nerve cells that transmit visual information to the brain. Intra-Ocular Pressure (IOP) is the most significant danger reason to develop glaucoma. Even though a number of variables, including various optic disc parameters, have been used to discover early glaucoma damage, there is a real need for computer-aided detection (CAD) me...

Paperback: 132 pages
Publisher: LAP LAMBERT Academic Publishing (August 4, 2011)
Language: English
ISBN-10: 384542821X
ISBN-13: 978-3845428215
Product Dimensions: 5.9 x 0.3 x 8.7 inches
Format: PDF ePub fb2 djvu ebook

Give yourself the gift of self-care, and read this guidebook to get you started. My only minor complaint is that I had to use a magnifying glass to read the hand written letters LOL. ebook Automated Diagnosis Of Glaucoma Using Ai Techniques: Neural Networks, Decision Trees, Naïve Bayes, And Support Vector Machine Pdf Epub. The only useful info was a list and brief description of each of the more popular pricing tools, scouting apps, etc. He's pulling out the stops because he's sure India's the woman for him and his best friend and business partner, Marc Jasper. It's a month before Christmas and Kris Kringle (Santa Claus) has decided there is too much greed in the world. The book must provide an original contribution to the field. A few days later the price was dropped to $9. The title reflected the inner pain and turmoil that he may have gone through in the short life he lived, to live by his own high standards of honesty. Joyce's writing is lyrical, intimate and insightful. This book has been treated unevenly by reviewers.

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can identify early glaucomatous development so that treatment to avoid further progression can be started especially in mass screenings, because ophthalmologists have limited time to assess mass number of fundus images.This thesis focused on the description of a system based on image processing and classification techniques for the estimation of quantitative parameters to classify fundus images into two classes: glaucoma patients and normal patients.