Computer-Assisted Screening for Cervical Cancer Using Digital Image Processing of Pap Smear Images [PDF]
Applied Sciences, 2020 Cervical cancer can be prevented by having regular screenings to find any precancers and treat them. The Pap test looks for any abnormal or precancerous changes in the cells on the cervix.
Kyi Pyar Win +3 more
doaj +4 more sources
Bias in machine learning for computer-assisted surgery and medical image processing [PDF]
Computer Assisted Surgery, 2022 John S. H. Baxter, Pierre Jannin
doaj +5 more sources
Computer-Assisted Image Processing System for Early Assessment of Lung Nodule Malignancy [PDF]
Cancers, 2022 Lung cancer is one of the most dreadful cancers, and its detection in the early stage is very important and challenging. This manuscript proposes a new computer-aided diagnosis system for lung cancer diagnosis from chest computed tomography scans.
Ahmed Shaffie +4 more
openaire +3 more sources
Computer-assisted image processing to detect spores from the fungus Pandora neoaphidis
MethodsX, 2016 This contribution demonstrates an example of experimental automatic image analysis to detect spores prepared on microscope slides derived from trapping. The application is to monitor aerial spore counts of the entomopathogenic fungus Pandora neoaphidis which may serve as a biological control agent for aphids.
Korsnes, Reinert +3 more
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Computer-Assisted Bone Age Assessment: Graphical User Interface for Image Processing and Comparison [PDF]
Journal of Digital Imaging, 2004 The current study is part of a project resulting in a computer-assisted analysis of a hand radiograph yielding an assessment of skeletal maturity. The image analysis is based on features selected from six regions of interest. At various stages of skeletal development different image processing problems have to be addressed.
Fei Cao +5 more
openaire +3 more sources
Computer-assisted, interactive fundus image processing for macular drusen quantitation
Ophthalmology, 1999 To design and validate a software package to quantitate the area subtended by drusen in color fundus photographs for the conduct of efficient, accurate clinical trials in age-related macular degeneration.Algorithm and software development. Comparisons with manual methodologies.Evaluation and testing on color fundus photographs from patient records and ...
Noreen B. Javornik +2 more
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Computer-assisted analysis of painting brushstrokes: digital image processing for unsupervised extraction of visible features from van Gogh’s works [PDF]
EURASIP Journal on Image and Video Processing, 2014 AbstractThe automatic extraction of objective features from paintings, like brushstroke distribution, orientation, and shape, could be particularly useful for different artwork analyses and management tasks. In fact, these features contribute to provide a unique signature of the artists’ style and can be effectively used for artist identification and ...
LAMBERTI, FABRIZIO +2 more
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Evaluation of the Wider System, a New Computer-Assisted Image-Processing Device for Bacterial Identification and Susceptibility Testing [PDF]
Journal of Clinical Microbiology, 2000 ABSTRACT The Wider system is a newly developed computer-assisted image-processing device for both bacterial identification and antimicrobial susceptibility testing. It has been adapted to be able to read and interpret commercial MicroScan panels.
Begoña Sánchez Del Saz +6 more
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Digital mammography texture analysis by computer assisted image processing
2008 IEEE International Workshop on Imaging Systems and Techniques, 2008 We investigate the use of mammograms texture features in a clinical evaluation in mammography in order to assist in the classification of an image based on the breast tissue index. Breast tissue indices give the possibility to analyze images and determine the similarity of the images and evaluate the classification of the obtained image The measures of
S. Lyra +5 more
semanticscholar +5 more sources
Deep Learning Based Image Processing for Robot Assisted Surgery: A Systematic Literature Survey
IEEE Access, 2022 The recent advancements in the surging field of Deep Learning (DL) have revolutionized every sphere of life, and the healthcare domain is no exception. The enormous success of DL models, particularly with image data, has led to the development of image ...
Sardar Mehboob Hussain +5 more
semanticscholar +1 more source