Automatic Measurement of Blood Vessel Angles in Immunohistochemical Images of Liver Cancer
نویسندگان
چکیده
Measurement of vascular angle is a key step in quantitative analysis of immunohistochemistry. This paper presents a method for automated measurement of vascular angle in immunohistochemical images of liver cancer. Firstly, Colour Deconvolution is used to conduct stain separation on a H&Estained immunohistochemical image,and then blood vessels are segmented using an improved Otsu algorithm. Then the standard SURF algorithm is used to select feature points of the image, and then these feature points are divided into two equal groups according to the distance between individual feature points and the far left (or right) feature point. Finally, a standard least squares method is used to fit two lines using the two group of points. When the linear deviation of the fitting result based on the two groups of feature points is significant, it is necessary to adjust the belonging of the points of the two groups, and then the two sets are fitted again respectively till the correlation coefficients of the two fitted lines are greater than the predefined threshold, meaning that the measurement of the blood vessel angle in the immunohistochemical map is completed. In the experiments, 45 liver cancer images are used, where about 600 vessels are extracted. Compared with the experts’ results, our proposed technique results in better accuracy. It is worthy to point out that, to our knowledge, our system is the first one that conducts automated measurement of blood vessel angle of immunohistochemistry.
منابع مشابه
Automatic detection of liver tumor motion by fluoroscopy images
Background: A method to track liver tumor motion signals from fluoroscopic images without any implanted gold fiducial markers was proposed in this study to overcome the adverse effects on precise tumor irradiation caused by respiratory movement. Materials and Methods: The method was based on the following idea: (i) Before treatment, a series of fluoroscopic images corresponding to different bre...
متن کاملAutomatic measurement of instantaneous changes in the walls of carotid artery with sequential ultrasound images
Introduction: This study presents a computerized analyzing method for detection of instantaneous changes of far and near walls of the common carotid artery in sequential ultrasound images by applying the maximum gradient algorithm. Maximum gradient was modified and some characteristics were added from the dynamic programming algorithm for our applications. Methods: The algorithm was evaluat...
متن کاملSimulation study of Hemodynamic in Bifurcations for Cerebral Arteriovenous Malformation using Electrical Analogy
Background and Objective: Cerebral Arteriovenous Malformation (CAVM) hemodynamic is disease condition, results changes in the flow and pressure level in cerebral blood vessels. Measuring flow and pressure without catheter intervention along the vessel is big challenge due to vessel bifurcations/complex bifurcations in Arteriovenous Malformation patients. The vessel geometry in CAVM patients are...
متن کاملDetection of Blood Vessels in Color Fundus Images using a Local Radon Transform
Introduction: This paper addresses a method for automatic detection of blood vessels in color fundus images which utilizes two main tools: image partitioning and local Radon transform. Material and Methods: The input images are firstly divided into overlapping windows and then the Radon transform is applied to each. The maximum of the Radon transform in each window corresponds to the probable a...
متن کاملAutomatic classification of Non-alcoholic fatty liver using texture features from ultrasound images
Background: Accurate and early detection of non-alcoholic fatty liver, which is a major cause of chronic diseases is very important and is vital to prevent the complications associated with this disease. Ultrasound of the liver is the most common and widely performed method of diagnosing fatty liver. However, due to the low quality of ultrasound images, the need for an automatic and intelligent...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2017