Results 231 to 240 of about 277,259 (259)

Automated Image Interpretation and Computer-Assisted Diagnostics

open access: closed, 2013
Much of the difficulty in reaching consistent evaluations of radiology and pathology imaging studies arises from subjective impressions of individual observers. Developing strategies that can reliably transform complex visual observations into well-defined algorithmic procedures is an active area of exploration which can advance clinical practice ...
David J, Foran, Wenjin, Chen, Lin, Yang
openaire   +3 more sources

ON THE PROBLEM OF VALIDATING COMPUTER ASSISTED MEDICAL IMAGE INTERPRETATION

open access: closed, 1997
Hinging on approaches from the fields of clinical imaging and information technology assessment in medicine, a validation scheme is presented for 3-D biomedical image interpretation. This scheme considers measurement of algorithmic accuracy and evaluation of clinical functionality and usefulness.
null Van Cleynenbreugel Johan   +5 more
openaire   +2 more sources

Computer-assisted image interpretation: use of a neural network to differentiate tubular carcinoma from sclerosing adenosis.

open access: closedModern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc, 1992
Measurement of nuclear and glandular size and shape features was carried out on 18 cases of sclerosing adenosis and 18 cases of tubular carcinoma. Modified Bonferroni analysis showed that glandular surface density and the coefficient of variation of luminal form factor were significant in discriminating between these two lesions.
T J, O'Leary, U V, Mikel, R L, Becker
openaire   +2 more sources

[Computer-assisted diagnosis based on computer-based image interpretation and 3D-visualization].

Der Radiologe, 1998
To survey methods for 3D data visualization and image analysis which can be used for computer based diagnostics.The methods available are explained in short terms and links to the literature are presented. Methods which allow basic manipulation of 3D data are windowing, rotation and clipping.
D, Schuhmann   +7 more
openaire   +1 more source

Automated molecular-image cytometry and analysis in modern oncology

Nature Reviews Materials, 2020
Ralph Weissleder, Hakho Lee
exaly  

nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation

Nature Methods, 2020
Fabian Isensee   +2 more
exaly  

Ultrafast machine vision with 2D material neural network image sensors

Nature, 2020
Lukas Mennel   +2 more
exaly  

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