This study presents the development and evaluation of an image processing software for computer-assisted cellular structure counting. The proposed software consists of a set of processing and analytical tools which allows its use in several applications of cell and cellular structure counting. A particular application in AgNOR quantitative analysis is presented. The knowledge obtained from experienced pathologists has been codified in a sequence of processing steps in order to allow automatic estimation of the mean number of AgNORs per cell in ameloblastomas. The performance of the presented software in such application was verified by comparing the data provided by visual analysis, by two observers previously calibrated and under supervision of two experienced specialists (Group 1) and by the computer program (Group 2). No statistical difference was observed (p<0.05) between the two groups. The use of the proposed method in AgNOR applications permitted attainment of accurate and precise data without the difficulties frequently found in the traditional visual analysis method (time, training and subjectivity). The developed software is an interesting tool as an aid in the study (estimation of the number of cells and cellular structures) of malignant and benign neoplasms.
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http://dx.doi.org/10.1016/j.prp.2011.02.002 | DOI Listing |
Angew Chem Int Ed Engl
January 2025
Ruhr-Universität Bochum: Ruhr-Universitat Bochum, Inorganic Chemistry, Universitaetsstrasse 150, 44801, Bochum, GERMANY.
Precise control over low-dimensional materials holds an immense potential for their applications in sensing, imaging and information processing. The controlled introduction of sp3 quantum defects (color centers) can be used to tailor the optoelectronic properties of single-walled carbon nanotubes (SWCNTs) in the tissue transparency (> 800 nm) and the telecommunication window. However, an uncontrolled functionalization of SWCNTs with defects leads to a loss of the NIR fluorescence.
View Article and Find Full Text PDFArch Pathol Lab Med
January 2025
the Department of Pathology, The Ohio State University, Columbus (Parwani).
Context.—: Generative artificial intelligence (AI) has emerged as a transformative force in various fields, including anatomic pathology, where it offers the potential to significantly enhance diagnostic accuracy, workflow efficiency, and research capabilities.
Objective.
Mikrochim Acta
January 2025
Guizhou Province, Qianzhi Mingguang Soaphorn Rice Processing Base, Zhijin County, Maochang Town, Bijie CityBijie City, 552103, China.
A smartphone-based non-invasive method was developed for salivary uric acid detection using Gleditsia Sinensis carbon dots (GS-CDs). The GS-CDs synthesized by the one-pot hydrothermal method emitted blue fluorescence at a maximum excitation wavelength of 350 nm and had good fluorescence stability in the presence of different ions, while showing selectivity to uric acid solution. The ability of uric acid (UA) to quench the fluorescent substances present in the GS-CDs, was confirmed through HPLC-FLD and LC-MS, FTIR and XPS.
View Article and Find Full Text PDFMed Biol Eng Comput
January 2025
Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science, Suzhou, 215613, China.
Ultrasound blood flow imaging plays a crucial role in the diagnosis of cardiovascular and cerebrovascular diseases. Conventional ultrafast ultrasound plane-wave imaging techniques have limited capabilities in microvascular imaging. To enhance the quality of blood flow imaging, this study proposes a microbubble-based H-Scan ultrasound imaging technique.
View Article and Find Full Text PDFClin Oral Investig
January 2025
Department of Restorative Dentistry, School of Dentistry of Ribeirão Preto, University of São Paulo (USP), Ribeirão Preto, SP, Brazil.
Objectives: To evaluate cases of persistent apical periodontitis (PAP) and what are the imaging and clinical aspects that could be considered in the PAP diagnosis and in their treatment decision-making process.
Methodology: 423 patients with apical periodontitis at the time of non-surgical root canal treatment (NSRCT) were followed-up for at least 1 year. Periapical radiographic images were used to compare and determine periapical status at each time using the PAI scoring system.
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