Classification for breast cancer diagnosis with Raman spectroscopy.

Qingbo Li,Qishuo Gao,Guangjun Zhang

doi:10.1364/boe.5.002435

Abstract

In order to promote the development of the portable, low-cost and in vivo cancer diagnosis instrument, a miniature laser Raman spectrometer was employed to acquire the conventional Raman spectra for breast cancer detection in this paper. But it is difficult to achieve high discrimination accuracy. Then a novel method of adaptive weight k-local hyperplane (AWKH) is proposed to increase the classification accuracy. AWKH is an extension and improvement of K-local hyperplane distance nearest-neighbor (HKNN). It considers the features weights of the training data in the nearest neighbor selection and local hyperplane construction stage, which resolve the basic shortcoming of HKNN works well only for small values of the nearest-neighbor. Experimental results on Raman spectra of breast tissues in vitro show the proposed method can realize high classification accuracy.

Highlights

Breast cancer is one of the major causes of female death
Since the early diagnosis is the key factor to increase the rate of survival time for the cancer patients, it is important to develop fast, less invasive, objective methods for the diagnosis of breast cancers
Because these changes occur earlier than the clinical symptoms appearance and tumor medical imaging detection, molecular spectroscopy has the potential to early diagnosis of the tumor [3,4,5,6,7]

Summary

Introduction

Breast cancer is one of the major causes of female death. Data show 20% global increase in breast cancer from 2008 to 2012 [1]. Breast cancer accounts for 15% of all female cancer deaths, which is second only to lung cancer in the United States [2]. During the tumor formation, significant changes occurred in the structure and concentration of the main bimolecular, which constitute the cell and tissue, such as carbohydrates, lipids, proteins and nucleic acids. Because these changes occur earlier than the clinical symptoms appearance and tumor medical imaging detection, molecular spectroscopy has the potential to early diagnosis of the tumor [3,4,5,6,7]. Due to the characters such as sharp peaks, freeing from the interference of water, fewer samples required and without sample chemical treatment etc, Raman spectroscopy is promising to realize real-time and noninvasive detection at the molecular level

Methods

Results

Conclusion