Automatic analysis of tissue images
نویسنده
چکیده
Microscopy images can often be used for analysing the progression of the cancer by finding the proportion of cancer cells in a tissue after they have been stained with immunohistochemistry methods. When one has several such images it is better to analyse them automatically. This project aims to implement the averaged threshold method (ATM) which can be used to calculate the proportion of stained cells. For this I used EBImage package for R and analysed several images of breast cancer.
منابع مشابه
A Method for Body Fat Composition Analysis in Abdominal Magnetic Resonance Images Via Self-Organizing Map Neural Network
Introduction: The present study aimed to suggest an unsupervised method for the segmentation of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) in axial magnetic resonance (MR) images of the abdomen. Materials and Methods: A self-organizing map (SOM) neural network was designed to segment the adipose tissue from other tissues in the MR images. The segmentation of SAT and VA...
متن کاملA CAD System Framework for the Automatic Diagnosis and Annotation of Histological and Bone Marrow Images
Due to ever increasing of medical images data in the world’s medical centers and recent developments in hardware and technology of medical imaging, necessity of medical data software analysis is needed. Equipping medical science with intelligent tools in diagnosis and treatment of illnesses has resulted in reduction of physicians’ errors and physical and financial damages. In this article we pr...
متن کاملObject-Oriented Method for Automatic Extraction of Road from High Resolution Satellite Images
As the information carried in a high spatial resolution image is not represented by single pixels but by meaningful image objects, which include the association of multiple pixels and their mutual relations, the object based method has become one of the most commonly used strategies for the processing of high resolution imagery. This processing comprises two fundamental and critical steps towar...
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 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 کاملAutomatic Optic Disc Center and Boundary Detection in Color Fundus Images
Accurately detection of retinal landmarks, like optic disc, is an important step in the computer aided diagnosis frameworks. This paper presents an efficient method for automatic detection of the optic disc’s center and estimating its boundary. The center and initial diameter of optic disc are estimated by employing an ANN classifier. The ANN classifier employs visual features of vessels and th...
متن کامل