Automatic Breast Cancer Grading of Histopathological Images

被引：58

作者：

Dalle, Jean-Romain ^{[1
]}

Leow, Wee Kheng ^{[1
]}

Racoceanu, Daniel ^{[2
]}

Tutac, Adina Eunice ^{[3
]}

Putti, Thomas C. ^{[4
]}

机构：

[1] Natl Univ Singapore, Dept Comp Sci, Comp 1, Singapore 117590, Singapore

[2] IPAL, CNRS, UMI 2955, Singapore 119613, Singapore

[3] Univ Politecn Timisoara, Dept Engn, Timisoara, Romania

[4] Natl Univ Singapore Hosp, Dept Pathol, Singapore 119074, Singapore

来源：

2008 30TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-8 | 2008年

关键词：

D O I：

10.1109/IEMBS.2008.4649847

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Breast cancer grading of histopathological images is the standard clinical practice for the diagnosis and prognosis of breast cancer development. In a large hospital, a pathologist typically handles 100 grading cases per day, each consisting of about 2000 image frames. It is, therefore, a very tedious and time-consuming task. This paper proposes a method for automatic computer grading to assist pathologists by providing second opinions and reducing their workload. It combines the three criteria in the Nottingham scoring system using a multi-resolution approach. To our best knowledge, there is no existing work that provide complete grading according to the Nottingham criteria.

引用

页码：3052 / +

页数：3

共 50 条

[21] Multi-task deep learning for fine-grained classification and grading in breast cancer histopathological images
Li, Lingqiao
Pan, Xipeng
Yang, Huihua
Liu, Zhenbing
He, Yubei
Li, Zhongming
Fan, Yongxian
Cao, Zhiwei
Zhang, Longhao
MULTIMEDIA TOOLS AND APPLICATIONS, 2020, 79 (21-22) : 14509 - 14528
[22] Automatic Histological Grading of Breast Cancer Resection Tissue
Lee, Geongyu
Kim, Chung-Yeul
Kwak, Tae-Yeong
Kim, Sun Woo
Chang, Hyeyoon
MODERN PATHOLOGY, 2022, 35 (SUPPL 2) : 147 - 148
[23] Automatic Histological Grading of Breast Cancer Resection Tissue
Lee, Geongyu
Kim, Chung-Yeul
Kwak, Tae-Yeong
Kim, Sun Woo
Chang, Hyeyoon
LABORATORY INVESTIGATION, 2022, 102 (SUPPL 1) : 147 - 148
[24] Towards Automatic Classification of Breast Cancer Histopathological Image
Elelimy, E.
Mohamed, A. A.
PROCEEDINGS OF 2018 13TH INTERNATIONAL CONFERENCE ON COMPUTER ENGINEERING AND SYSTEMS (ICCES), 2018, : 299 - 306
[25] Classification and quantitative analysis of histopathological images of breast cancer
Anuranjeeta
Bhattacharjee, Romel
Sharma, Shiru
Shukla, K. K.
INTERNATIONAL JOURNAL OF BIOMEDICAL ENGINEERING AND TECHNOLOGY, 2021, 35 (03) : 263 - 293
[26] Feature Generalization for Breast Cancer Detection in Histopathological Images
Rik Das
Kanwalpreet Kaur
Ekta Walia
Interdisciplinary Sciences: Computational Life Sciences, 2022, 14 : 566 - 581
[27] Feature Generalization for Breast Cancer Detection in Histopathological Images
Das, Rik
Kaur, Kanwalpreet
Walia, Ekta
INTERDISCIPLINARY SCIENCES-COMPUTATIONAL LIFE SCIENCES, 2022, 14 (02) : 566 - 581
[28] Automated classification of breast cancer morphology in histopathological images
Ville Ojansivu
Nina Linder
Esa Rahtu
Matti Pietikäinen
Mikael Lundin
Heikki Joensuu
Johan Lundin
Diagnostic Pathology, 8 (Suppl 1)
[29] Adaptation of Deep Convolutional Neural Networks for Cancer Grading from Histopathological Images
Postavaru, Stefan
Stoean, Ruxandra
Stoean, Catalin
Joya Caparros, Gonzalo
ADVANCES IN COMPUTATIONAL INTELLIGENCE, IWANN 2017, PT II, 2017, 10306 : 38 - 49
[30] Computer analysis of histopathological images for tumor grading
Klonowski, Wlodzimierz
Korzynska, Anna
Gomolka, Ryszard
PHYSIOLOGICAL MEASUREMENT, 2018, 39 (03)

← 1 2 3 4 5 →