Name: Classification of Mammogram Images (en Inglés)
SKU: 62474005
Price: 58.40 USD
Availability: InStock
Author: Supriya Salve

portada Classification of Mammogram Images (en Inglés)

Classification of Mammogram Images (en Inglés)

Formato

Libro Físico

Editorial

Anchor Academic Publishing

Autor

Supriya Salve

Idioma

Inglés

N° páginas

Encuadernación

Tapa Blanda

ISBN13

9783960671411

Classification of Mammogram Images (en Inglés)

Supriya Salve (Autor) · Anchor Academic Publishing · Tapa Blanda

Libro Nuevo Importado

Envío: 25 a 32 días háb.

$ 106.17$ 58.40

-45%

Costos de importación incluídos en el precio ✅

Libro Nuevo

Quedan 10 unidades

$ 58.40

Llega entre el 25 Sep y el 08 Oct a Quito, Pichincha. Seleccionar ubicación

Agregar a lista de deseos

Reseña del libro "Classification of Mammogram Images (en Inglés)"

Breast cancer is the most common type of cancer in women, which also causes the most cancer deaths among them today. Mammography is the only reliable method to detect breast cancer in the early stage among all diagnostic methods available currently. Breast cancer can occur in both men and women and is defined as an abnormal growth of cells in the breast that multiply uncontrollably. The main factors which cause breast cancer are either hormonal or genetic. Masses are quite subtle, and have many shapes such as circumscribed, speculated or ill-defined. These tumors can be either benign or malignant. Computer-aided methods are powerful tools to assist the medical staff in hospitals and lead to better and more accurate diagnosis. The main objective of this research is to develop a Computer Aided Diagnosis (CAD) system for finding the tumors in the mammographic images and classifying the tumors as benign or malignant. There are five main phases involved in the proposed CAD system: image pre-processing, extraction of features from mammographic images using Gabor Wavelet and Discrete Wavelet Transform (DWT), dimensionality reduction using Principal Component Analysis (PCA) and classification using Support Vector Machine (SVM) classifier.