Automatic delineation of malignancy in histopathological head and neck slides

Background: Histopathology, which is one of the most important routines of all laboratory procedures used in pathology, is decisive for the diagnosis of cancer. Experienced histopathologists review the histological slides acquired from biopsy specimen in order to outline malignant areas. Recently, improvements in imaging technologies in terms of histological image analysis led to the discovery of virtual histological slides. In this technique, a computerized microscope scans a glass slide and generates virtual slides at a resolution of 0.25 μm/pixel. As the recognition of intrinsic cancer areas is time consuming and error prone, in this study we develop a novel method to tackle automatic squamous cell carcinoma of the head and neck detection problem in high-resolution, wholly-scanned histopathological slides. Results: A density-based clustering algorithm improved for this study plays a key role in the determination of the corrupted cell nuclei. Using the Support Vector Machines (SVMs...

• Type: Journal
• Year: 2007
• Where: BMCBI
• Authors: Mutlu Mete, Xiaowei Xu, Chun-Yang Fan, Gal Shafirstein
• Keywords: BMCBI 2007, Histological Slides, Histopathological Slides, Virtual Histological Slides