Color Swapping to Enhance Breast Cancer Digital Images Qualities Using Stain Normalization

被引：2

作者：

Muhimmah, Izzati ^{[1
]}

Wijaya, Dhina Puspasari ^{[2
]}

Indrayanti ^{[3
]}

机构：

[1] Univ Islam Indonesia, Dept Informat Engn, Jl Kaliurang Km 14, Yogyakarta 55510, Indonesia

[2] Univ Islam Indonesia, Informat Engn, Jl Kaliurang Km 14, Yogyakarta 55510, Indonesia

[3] Univ Muhammadiyah Yogyakarta, Fac Med & Hlth Sci, Jl Kaliurang Km 14, Yogyakarta 55510, Indonesia

来源：

INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND DIGITAL APPLICATIONS | 2017年 / 185卷

关键词：

D O I：

10.1088/1757-899X/185/1/012029

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Histopathology is the disease diagnosis by means of the visual examination of tissues under the microscope. The virtually transparent tissue sections were prepared using a number of colored histochemical stains bound selectively to the cellular components. A variation of colors comes to be a problem in histopathology based upon the microscope lighting for the range of factors. This research aimed to investigate an image enhancement by applying a nonlinear mapping approach to stain normalization and histogram equalization for contrast enhancement. Validation was carried out in 59 datasets with 96.6% accordance and expert justification.

引用

页数：7

共 50 条

[1] A stain color normalization with robust dictionary learning for breast cancer histological images processing
Tosta, Thaina A. Azevedo
Freitas, Andre Dias
de Faria, Paulo Rogerio
Neves, Leandro Alves
Martins, Alessandro Santana
do Nascimento, Marcelo Zanchetta
[J]. BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2023, 85
[2] Stain Normalization in Digital Pathology Images Using Deep Learning
Janowczyk, Andrew
Basavanhally, Ajay
Madabhushi, Anant
[J]. MODERN PATHOLOGY, 2016, 29 : 395A - 395A
[3] Stain Normalization in Digital Pathology Images Using Deep Learning
Janowczyk, Andrew
Basavanhally, Ajay
Madabhushi, Anant
[J]. LABORATORY INVESTIGATION, 2016, 96 : 395A - 395A
[4] Automated Classification for Breast Cancer Histopathology Images: Is Stain Normalization Important?
Gupta, Vibha
Singh, Apurva
Sharma, Kartikeya
Bhavsar, Arnav
[J]. COMPUTER ASSISTED AND ROBOTIC ENDOSCOPY AND CLINICAL IMAGE-BASED PROCEDURES, 2017, 10550 : 160 - 169
[5] A Nonlinear Mapping Approach to Stain Normalization in Digital Histopathology Images Using Image-Specific Color Deconvolution
Khan, Adnan Mujahid
Rajpoot, Nasir
Treanor, Darren
Magee, Derek
[J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2014, 61 (06) : 1729 - 1738
[6] Structure-Preserving Color Normalization and Sparse Stain Separation for Histological Images
Vahadane, Abhishek
Peng, Tingying
Sethi, Amit
Albarqouni, Shadi
Wang, Lichao
Baust, Maximilian
Steiger, Katja
Schlitter, Anna Melissa
Esposito, Irene
Navab, Nassir
[J]. IEEE TRANSACTIONS ON MEDICAL IMAGING, 2016, 35 (08) : 1962 - 1971
[7] STAIN NORMALIZATION OF HISTOPATHOLOGY IMAGES USING GENERATIVE ADVERSARIAL NETWORKS
Zanjani, Farhad Ghazvinian
Zinger, Svitlana
Bejnordi, Babak Ehteshami
van der Laak, Jeroen A. W. M.
de With, Peter H. N.
[J]. 2018 IEEE 15TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2018), 2018, : 573 - 577
[8] Deep Convolutional Gaussian Mixture Model for Stain-Color Normalization of Histopathological Images
Zanjani, Farhad Ghazvinian
Zinger, Svitlana
de With, Peter H. N.
[J]. MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2018, PT II, 2018, 11071 : 274 - 282
[9] DOMAIN ADAPTATION OF DIGITAL PATHOLOGY IMAGES USING JOINT STAIN COLOR AND IMAGE QUALITY CONSTRAINTS
Long, Xi
Liu, Jingxin
Hou, Xianxu
[J]. 2023 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP, 2023, : 1805 - 1809
[10] Single Generative Networks for Stain Normalization and Quality Enhancement of Histological Images in Digital Pathology
Mao, Xintian
Wang, Jiansheng
Tao, Xiang
Wang, Yan
Li, Qingli
Zhou, Xiufeng
Zhang, Yonghe
[J]. 2021 14TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, BIOMEDICAL ENGINEERING AND INFORMATICS (CISP-BMEI 2021), 2021,

← 1 2 3 4 5 →