Background: Virtual microscopy includes digitisation of histology slides and the use of computer technologies for complex investigation of diseases such as cancer. However, automated image analysis, or website publishing of such digital images, is hampered by their large file sizes.
Results: We have developed two Java based open source tools: Snapshot Creator and NDPI-Splitter. Snapshot Creator converts a portion of a large digital slide into a desired quality JPEG image. The image is linked to the patient's clinical and treatment information in a customised open source cancer data management software (Caisis) in use at the Australian Breast Cancer Tissue Bank (ABCTB) and then published on the ABCTB website (http://www.abctb.org.au) using Deep Zoom open source technology. Using the ABCTB online search engine, digital images can be searched by defining various criteria such as cancer type, or biomarkers expressed. NDPI-Splitter splits a large image file into smaller sections of TIFF images so that they can be easily analysed by image analysis software such as Metamorph or Matlab. NDPI-Splitter also has the capacity to filter out empty images.
Conclusions: Snapshot Creator and NDPI-Splitter are novel open source Java tools. They convert digital slides into files of smaller size for further processing. In conjunction with other open source tools such as Deep Zoom and Caisis, this suite of tools is used for the management and archiving of digital microscopy images, enabling digitised images to be explored and zoomed online. Our online image repository also has the capacity to be used as a teaching resource. These tools also enable large files to be sectioned for image analysis.
Virtual Slides: The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/5330903258483934.
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http://dx.doi.org/10.1186/1746-1596-8-22 | DOI Listing |
Arch Dermatol Res
January 2025
Department of Dermatology, Drexel University College of Medicine, 860 1St Avenue, Suite 8B, Philadelphia, PA, 19406, USA.
UV-A exposure is a major risk factor for melanoma, nonmelanoma skin cancer, photoaging, and exacerbation of photodermatoses. Since people spend considerable time in cars daily, inadequate UV-A attenuation by car windows can significantly contribute to the onset or exacerbation of these skin diseases. Given recent market trends in the automobile industry and known impact of car windows on cumulative lifelong UV damage to the skin, there is a need to comparatively evaluate UV transmission across windows in electric vehicles (EV), hybrid vehicles (HV), and gas vehicles (GV) as well as variability based on year of manufacture and mileage to inform car manufacturers and consumers of the potential for UV exposure to the skin based on vehicle.
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January 2025
American Hip Institute Research Foundation, Des Plaines, Illinois, USA.
Background: Sex has been associated with different pathologic characteristics in painful hips undergoing hip arthroscopic surgery.
Purpose: To compare minimum 10-year patient-reported outcomes (PROs) and survivorship in patients who underwent primary hip arthroscopic surgery for femoroacetabular impingement syndrome and labral tears according to sex.
Study Design: Cohort study; Level of evidence, 3.
BMC Public Health
January 2025
Epidemiology Program, Institute of Health Sciences, Istanbul Medipol University, Istanbul, Türkiye.
Introduction: This study aims to investigate the knowledge, attitudes, and behaviors of Syrian migrant women regarding breast and cervical cancer screenings in the Sultanbeyli district of Istanbul.
Methods: The women were recruited from Extended Migrant Health Centre, which is a primary health care institution in Istanbul. In August 2024, face-to-face interviews were conducted using an open-ended, semi-structured question form administered by a nurse experienced in qualitative research.
BMC Med Res Methodol
January 2025
Biostatistics Research Group, Department of Population Health Sciences, University of Leicester, Leicester, UK.
Background: Since 2015, the Complex Reviews Synthesis Unit (CRSU) has developed a suite of web-based applications (apps) that conduct complex evidence synthesis meta-analyses through point-and-click interfaces. This has been achieved in the R programming language by combining existing R packages that conduct meta-analysis with the shiny web-application package. The CRSU apps have evolved from two short-term student projects into a suite of eight apps that are used for more than 3,000 h per month.
View Article and Find Full Text PDFNPJ Digit Med
January 2025
School of Mechanical Engineering, Shandong University, Jinan, China.
Extensive research on retinal layer segmentation (RLS) using deep learning (DL) is mostly approaching a performance plateau, primarily due to reliance on structural information alone. To address the present situation, we conduct the first study on the impact of multi-spectral information (MSI) on RLS. Our experimental results show that incorporating MSI significantly improves segmentation accuracy for retinal layer optical coherence tomography (OCT) images.
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