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Classifying Chest Pathology Images Using Deep Learning Techniques

Name: Classifying Chest Pathology Images Using Deep Learning Techniques
Brand: LAP LAMBERT Academic Publishing
SKU: 9786203027211
Price: 789 CZK
Availability: InStock

Autor: Vrushali Dhanokar

Jazyk:

Vazba: Brožovaná

Vydavatel: LAP LAMBERT Academic Publishing

Dostupnost: Skladem u dodavatele

Odesíláme za 5-8 dnů

789 Kč

Chest radiographs are the most common examination in radiology in today's era. They are essential an...

Informace o knize

Autor

Vrushali Dhanokar

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

2020

Stránek

EAN

9786203027211

ISBN

6203027219

Enbook ID

36911110

Vydavatel

LAP LAMBERT Academic Publishing

Hmotnost

119

Rozměry

150 x 220 x 4

Kompletní popis

Chest radiographs are the most common examination in radiology in today's era. They are essential and very helpful for the supervision of various diseases associated with high mortality and display a wide range of potential information about various diseases. The most common verdicts in chest X-rays include Tuberculosis, Cardiomegaly & Mediastinum chest diseases. Distinguishing the various chest pathologies is a difficult task even to the human observer and for radiologist. Therefore, there is an interest in developing computer system diagnosis to assist radiologists in reading chest images through machine. The healthy versus pathology detection i.e. Tuberculosis and Cardiomegaly in chest radiography was explored using Laplacian of Gaussian (LoG), Local Binary Patterns (LBP), Speed up Robust Features (SURF) and also used the Bag-of-Visual-Words (BoVW) model using Artificial Neural Network (ANN) & Deep Learning techniques that classifies between healthy vs pathological cases.