Hyperspectral imaging for diagnosis and detection of ex-vivo breast cancer.

Aboughaleb, Ibrahim H; Aref, Mohamed Hisham; El-Sharkawy, Yasser H

BACKGROUND AND PURPOSE Breast cancer is one of the most widely recognized harmful tumors in the entire world and the main source of death among women. Where, early cancer diagnostic and treatment very critical for live-saving, leading to patient better prognosis and successful full recovery. During the most recent couple of decades, numerous examinations have been performed on the early discovery of malignant growth utilizing noninvasive or light intrusive methods in lieu of conventional excisional biopsy. MATERIALS AND METHODS The change of the optical properties of ex-vivo breast tissues provides different responses to light transmission, absorption, and particularly the reflection over the spectrum range. We offer the use of Hyperspectral imaging (HSI) with advanced image processing and pattern recognition in order to analyze HSI data for breast cancer detection. The spectral signatures were mined and evaluated in both malignant and normal tissue. K-mean clustering was designed for classifying hyperspectral data in order to evaluate and detection of cancer tissue. This method was used to detect ex-vivo breast cancer. Spatial spectral images were created to high spot the differences in the reflectance properties of malignant versus normal tissue. RESULTS Trials showed that the superficial spectral reflection images within 500 nm wavelength showed high variance (214.65) between cancerous and normal breast tissues. On the other hand, image within 620 nm wavelength showed low variance (0.0020).However, the superimposed of spectral region 420-620 nm was proposed as the optimum bandwidth. Finally, the proposed HS imaging system was capable to discriminate the tumor region from normal tissue of the ex-vivo breast sample with sensitivity and a specificity of 95 % and 96 %. CONCLUSIONS High sensitivity and specificity were achieved, which proposes potential for HSI as an edge evaluation method to enhance the surgical outcome compared to the presently available techniques in the clinics.