Mitosis detection in breast cancer histological images based on texture features using AdaBoost
Journal Title: Journal of Information Systems and Telecommunication - Year 2017, Vol 5, Issue 2
Abstract
Counting mitotic figures present in tissue samples from a patient with cancer, plays a crucial role in assessing the patient’s survival chances. In clinical practice, mitotic cells are counted manually by pathologists in order to grade the proliferative activity of breast tumors. However, detecting mitoses under a microscope is a labourious, time-consuming task which can benefit from computer aided diagnosis. In this research we aim to detect mitotic cells present in breast cancer tissue, using only texture and pattern features. To classify cells into mitotic and non-mitotic classes, we use an AdaBoost classifier, an ensemble learning method which uses other (weak) classifiers to construct a strong classifier. 11 different classifiers were used separately as base learners, and their classification performance was recorded. The proposed ensemble classifier is tested on the standard MITOS-ATYPIA-14 dataset, where a pixel window around each cells center was extracted to be used as training data. It was observed that an AdaBoost that used Logistic Regression as its base learner achieved a F1 Score of 0.85 using only texture features as input which shows a significant performance improvement over status quo. It also observed that "Decision Trees" provides the best recall among base classifiers and "Random Forest" has the best Precision.
Authors and Affiliations
Sooshiant Zakariapour, Hamid Jazayeriy, Mehdi Ezoji
Keywords
Related Articles
- EP ID EP211820
- DOI -
- Views 129
- Downloads 0
Crisis management using spatial query processing in wireless sensor networks
Natural disasters are an inevitable part of the world that we inhabit. Human casualties and financial losses are concomitants of these natural disasters. However, by an efficient crisis management program, we can minimiz...
Automatic Construction of Domain Ontology Using Wikipedia and Enhancing it by Google Search Engine
The foundation of the Semantic Web are ontologies. Ontologies play the main role in the exchange of information and development of the Lexical Web to the Semantic Web. Manual construction of ontologies is time-consuming,...
Image Retrieval Using Color-Texture Features Extracted From Gabor-Walsh Wavelet Pyramid
Image retrieval is one of the most applicable image processing techniques which have been extensively used. Feature extraction is one of the most important procedures used for interpretation and indexing images in Conten...
Detection and Removal of Rain from Video Using Predominant Direction of Gabor Filters
In this paper, we examine the visual effects of rain on the imaging system and present a new method for detection and removal of rain in a video sequences. In the proposed algorithm, to separate the moving foreground fro...
Online Signature Verification: a Robust Approach for Persian Signatures
In this paper, the specific trait of Persian signatures is applied to signature verification. Efficient features, which can discriminate among Persian signatures, are investigated in this approach. Persian signatures, in...