Automated Protein Localization of Blood Brain Barrier Vasculature in Brightfield IHC Images.
Where this comes from
- Record sourced from PubMed, PMID 26828723.
- Also identified by DOI 10.1371/journal.pone.0148411 and PMC identifier 4734698.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
In this paper, we present an objective method for localization of proteins in blood brain barrier (BBB) vasculature using standard immunohistochemistry (IHC) techniques and bright-field microscopy. Images from the hippocampal region at the BBB are acquired using bright-field microscopy and subjected to our segmentation pipeline which is designed to automatically identify and segment microvessels containing the protein glucose transporter 1 (GLUT1). Gabor filtering and k-means clustering are employed to isolate potential vascular structures within cryosectioned slabs of the hippocampus, which are subsequently subjected to feature extraction followed by classification via decision forest. The false positive rate (FPR) of microvessel classification is characterized using synthetic and non-synthetic IHC image data for image entropies ranging between 3 and 8 bits. The average FPR for synthetic and non-synthetic IHC image data was found to be 5.48% and 5.04%, respectively.
Medical subject headings
- Blood-Brain Barrier
- Glucose Transporter Type 1
- Image Processing, Computer-Assisted
- Microvessels