Evaluation of FISH image analysis system on assessing HER2 amplification in breast carcinoma cases.

HER2-positive breast cancer is characterized by aggressive growth and poor prognosis. Women with metastatic breast cancer with over-expression of HER2 protein or excessive presence of HER2 gene copies are potential candidates for Herceptin (Trastuzumab) targeted treatment that binds to HER2 receptors on tumor cells and inhibits tumor cell growth. Fluorescence in situ hybridization (FISH) is one of the most widely used methods to determine HER2 status. Typically, evaluation of FISH images involves manual counting of FISH signals in multiple images, a time consuming and error prone procedure. Recently, we developed novel software for the automated evaluation of FISH images and, in this study, we present the first testing of this software on images from two separate research clinics. To our knowledge, this is the first concurrent evaluation of any FISH image analysis software in two different clinics. The evaluation shows that the developed FISH image analysis software can accelerate evaluation of HER2 status in most breast cancer cases.

Airborne asbestos fibers detection in microscope images using re-initialization free active contours.

Breathing in asbestos fibers can lead to a number of diseases, the fibers become trapped in the lung and cannot be removed by either coughing or the person's immune system. Atmospheric concentrations of carcinogenic asbestos fibers, have traditionally been measured visually using phase contrast microscopy. However, because this measurement method requires great skill, and has poor reproducibility and objectivity, the development of automatic counting methods has been long anticipated. In this paper we proposed an automated fibers detection method based on a variational formulation of geometric active contours that forces the level set function to be close to signed distance function and therefore completely eliminates the need of the costly re-initialization procedure. The method was evaluated using a ground truth of 29 manually annotated images. The results were encouraging for the further development of the proposed method.

Automated analysis of FISH and immunohistochemistry images: a review.

Fluorescent in-situ hybridization (FISH) and immunohistochemistry (IHC) constitute a pair of complimentary techniques for detecting gene amplification and overexpression, respectively. The advantages of IHC include relatively cheap materials and high sample durability, while FISH is the more accurate and reproducible method. Evaluation of FISH and IHC images is still largely performed manually, with automated or semiautomated techniques increasing in popularity. Here, we provide a comprehensive review of a number of (semi-) automated FISH and IHC image processing systems, focusing on the algorithmic aspects of each technique. Our review verifies the increasingly important role of such methods in FISH and IHC; however, manual intervention is still necessary in order to resolve particularly challenging or ambiguous cases. In addition, large-scale validation is required in order for these systems to enter standard clinical practice.