A software framework for diagnostic medical image perception with feedback and a novel perception visualization technique
PW Phillips, DJ Manning, T Donovan… - … : Image Perception …, 2005 - spiedigitallibrary.org
… 1 but in medical imaging it is primarily used as a tool for measuring and understanding
perception when related to observer performance. Using an eye tracker to record eye movements …
perception when related to observer performance. Using an eye tracker to record eye movements …
Retinal model-based visual perception: applied for medical image processing
T Rajalakshmi, S Prince - Biologically Inspired Cognitive Architectures, 2016 - Elsevier
… This paper presents the comparative study of various quality metrics for medical image
processing application. The proposed work is based on Benoit et al. (2010) but modified …
processing application. The proposed work is based on Benoit et al. (2010) but modified …
[引用][C] Update on long-term goals for medical image perception research
EA Krupinski, HL Kundel - Academic Radiology, 1998 - Elsevier
… In the field of medical image perception, we are generally concerned with studying
observer performance in terms of diagnostic decisions. Over the years, the receiver operating …
observer performance in terms of diagnostic decisions. Over the years, the receiver operating …
A new software tool for removing, storing, and adding abnormalities to medical images for perception research studies
MT Madsen, KS Berbaum, AN Ellingson… - Academic radiology, 2006 - Elsevier
… The seamless removal of undesired abnormal areas and placement of proven abnormalities
described in this paper allows CT and other medical images to be used for perception …
described in this paper allows CT and other medical images to be used for perception …
Establishing perceptual limits for medical image compression
… for perceived image quality over three different image modality collections, using test sets of
5 images from … The results indicate a smooth decrease in perceived image quality in all three …
5 images from … The results indicate a smooth decrease in perceived image quality in all three …
Visual illusions in radiology: untrue perceptions in medical images and their implications for diagnostic accuracy
RG Alexander, F Yazdanie, S Waite… - Frontiers in …, 2021 - frontiersin.org
… structures on medical images, ie, by enhancing boundary perception. Examples include any
objects or surfaces where their physical luminance differs from their perceived brightness or …
objects or surfaces where their physical luminance differs from their perceived brightness or …
Vispi: Automatic visual perception and interpretation of chest x-rays
… Medical imaging contains the essential information for rendering diagnostic and treatment
decisions. Inspecting (visual perception) and interpreting image … an automatic medical image …
decisions. Inspecting (visual perception) and interpreting image … an automatic medical image …
User's image perception improved strategy and application of augmented reality systems in smart medical care: A review
J Jiang, J Zhang, J Sun, D Wu… - … Journal of Medical …, 2023 - Wiley Online Library
… the medical field because they can provide doctors with clear enough medical images and
accurate image … on doctors' perception of the image after virtual-real fusion during the actual …
accurate image … on doctors' perception of the image after virtual-real fusion during the actual …
[HTML][HTML] Medical image perception: how much do we understand it?
… in accurate medical image perception and to date the medical image perception and vision
… by the concurrent special issues relating to medical image perception such as this Topic (…
… by the concurrent special issues relating to medical image perception such as this Topic (…
A survey on deep learning in medical image analysis
… medical images. This paper reviews the major deep learning concepts pertinent to medical
image analysis … We survey the use of deep learning for image classification, object detection, …
image analysis … We survey the use of deep learning for image classification, object detection, …