Quantitative validation of anti‐PTBP1 antibody for diagnostic neuropathology use: Image analysis approach

E Goceri, B Goksel, JB Elder… - … journal for numerical …, 2017 - Wiley Online Library
Traditional diagnostic neuropathology relies on subjective interpretation of visual data
obtained from a brightfield microscopy. This approach causes high variability, unsatisfactory …

Automated fluorescent miscroscopic image analysis of PTBP1 expression in glioma

B Kaya, E Goceri, A Becker, B Elder, V Puduvalli… - Plos one, 2017 - journals.plos.org
Multiplexed immunofluorescent testing has not entered into diagnostic neuropathology due
to the presence of several technical barriers, amongst which includes autofluorescence. This …

High-accuracy automated diagnosis of Parkinson's disease

I Ozsahin, B Sekeroglu, PC Pwavodi… - Current Medical …, 2020 - ingentaconnect.com
Purpose: Parkinson's disease (PD), which is the second most common neurodegenerative
disease following Alzheimer's disease, can be diagnosed clinically when about 70% of the …

Differentiating early and late stage Parkinson's disease patients from healthy controls

D Mudali, M Biehl, SK Meles, RJ Renken… - Journal of Biomedical …, 2016 - research.rug.nl
Differentiating Early and Late Stage Parkinson’s Disease Patients from Healthy Controls — the
University of Groningen research portal Skip to main navigation Skip to search Skip to main …

Brain tumor classification based on hybrid approach

W Ayadi, I Charfi, W Elhamzi, M Atri - The Visual Computer, 2022 - Springer
Various computer systems have attracted more researchers' attention to arrive at a
qualitative diagnosis in a few times. Different brain tumor classification approaches are …

Advanced morphological technique for automatic brain tumor detection and evaluation of statistical parameters

K Sudharani, TC Sarma, KS Prasad - Procedia Technology, 2016 - Elsevier
A tumor is uncontrolled growth of the abnormal tissue in the body. If this phenomenon is in
brain is brain tumor. A tumor may lead to cancer. Image processing techniques are applied …

[PDF][PDF] Diagnosis of brain tumor using combination of K-means clustering and genetic algorithm

L Zeinalkhani, AA Jamaat… - Frontiers in Health …, 2018 - healthinformaticsjournal.com
Introduction: Medical image processing aimed at reducing human error rates attracted many
researchers. The Segmentation of magnetic resonance image for tumor detection is one of …

[PDF][PDF] Brain tumor detection using neural network

P Sapra, R Singh, S Khurana - International Journal of Science and …, 2013 - ijisme.org
The segmentation of brain tumors in magnetic resonance images (MRI) is a challenging and
difficult task because of the variety of their possible shapes, locations, image intensities. In …

Code-free machine learning for classification of central nervous system histopathology images

P Jungo, E Hewer - Journal of Neuropathology & Experimental …, 2023 - academic.oup.com
Abstract Machine learning (ML), an application of artificial intelligence, is currently
transforming the analysis of biomedical data and specifically of biomedical images including …

Computer-aided diagnosis of Parkinson's disease based on [123I] FP-CIT SPECT binding potential images, using the voxels-as-features approach and support vector …

FPM Oliveira, M Castelo-Branco - Journal of neural engineering, 2015 - iopscience.iop.org
Objective. The aim of the present study was to develop a fully-automated computational
solution for computer-aided diagnosis in Parkinson syndrome based on [123 I] FP-CIT single …