Effective histopathological image area reduction method for real-time applications

Küçük Resim Yok

Tarih

2018

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

IS&T & SPIE

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

Histopathologic images are time consuming for both specialist and machine learning methods with their complex structure and huge dimensions. In these cases, delays in the diagnosis of disease occur, as well as the treatment of fewer patients. When the histopathological images are examined at low resolution for shortening the examination time, it is almost impossible to identify the cancerous regions. When examining high-resolution images, it takes a long time to inspect because the image is divided into patches. Despite the fact that fairly fast machine learning methods are offered for the shortening of the analysis period, the number of patches to be examined has a negative effect on the decision time. For this reason, the area under examination needs to be reduced. For this, first of all, the destruction of cell-free areas and then the destruction of areas containing noncancerous cells must be eliminated. An effective and fast method of area reduction is presented for faster analysis and real-time use of histopathological images by machine learning algorithms. A two-step approach is used in the proposed method. In the first step, 3 x 3 texture properties of images are obtained and discrete wavelet transform is applied. Then, the image is cleaned with simple morphological processes. In the second step, the cleaned image is subjected to a discrete wavelet transform. Thus, the changes in cell-containing regions are captured, and regions that may be dangerous are identified. The proposed method reduced the areas to be examined by 98.5% to 99.5% with 95.33% accuracy. (C) 2018 SPIE and IS&T

Açıklama

Anahtar Kelimeler

dimension reduction, discrete wavelet transform, histopathological image classification, texture analysis

Kaynak

JOURNAL OF ELECTRONIC IMAGING

WoS Q Değeri

Q4

Scopus Q Değeri

Q3

Cilt

27

Sayı

5

Künye