AutoTag and AutoSnap: Standardized, semi-automatic capture of regions of interest from whole slide images
نویسندگان
چکیده
Tumor angiogenesis is measured by counting microvessels in tissue sections at high power magnification as a potential prognostic or predictive biomarker. Until now, regions of interest (ROIs) were selected by manual operations within a tumor by using a systematic uniform random sampling (SURS) approach. Although SURS is the most reliable sampling method, it implies a high workload. However, SURS can be semi-automated and in this way contribute to the development of a validated quantification method for microvessel counting in the clinical setting. Here, we report a method to use semi-automated SURS for microvessel counting: •Whole slide imaging with Pannoramic SCAN (3DHISTECH)•Computer-assisted sampling in Pannoramic Viewer (3DHISTECH) extended by two self-written AutoHotkey applications (AutoTag and AutoSnap)•The use of digital grids in Photoshop(®) and Bridge(®) (Adobe Systems) This rapid procedure allows traceability essential for high throughput protein analysis of immunohistochemically stained tissue.
منابع مشابه
Development and Validation of a Histological Method to Measure Microvessel Density in Whole-Slide Images of Cancer Tissue
Despite all efforts made to develop predictive biomarkers for antiangiogenic therapies, no unambiguous markers have been identified so far. This is due to among others the lack of standardized tests. This study presents an improved microvessel density quantification method in tumor tissue based on stereological principles and using whole-slide images. Vessels in tissue sections of different can...
متن کاملSalient regions detection in satellite images using the combination of MSER local features detector and saliency models
Nowadays, due to quality development of satellite images, automatic target detection on these images has been attracted many researchers' attention. Remote-sensing images follow various geospatial targets; these targets are generally man-made and have a distinctive structure from their surrounding areas. Different methods have been developed for automatic target detection. In most of these met...
متن کاملAutomatic Interpretation of UltraCam Imagery by Combination of Support Vector Machine and Knowledge-based Systems
With the development of digital sensors, an increasing number of high-resolution images are available. Interpretation of these images is not possible manually, which necessitates seeking for practical, fast and automatic solutions to solve the environmental and location-based management problems. The land cover classification using high-resolution imagery is a difficult process because of the c...
متن کاملAutomatic segmentation of glioma tumors from BraTS 2018 challenge dataset using a 2D U-Net network
Background: Glioma is the most common primary brain tumor, and early detection of tumors is important in the treatment planning for the patient. The precise segmentation of the tumor and intratumoral areas on the MRI by a radiologist is the first step in the diagnosis, which, in addition to the consuming time, can also receive different diagnoses from different physicians. The aim of this study...
متن کاملUtility of 123I-MIBG Standardized Uptake Value in Patients with Refractory Pheochromocytoma and Paraganglioma
Objective(s): Single-photon emission computed tomography (SPECT) using metaiodobenzylguanidine (MIBG) is an important diagnostic tool for the treatment of refractory pheochromocytoma and paraganglioma (PPGL). Owing to the difficulty of SPECT quantification, the tumour-to-background ratio (TBR) is used to assess disease activity. However, the utility of TBR is limited o...
متن کامل