3 research outputs found
Query by image medical training: optical biopsy with confocal endoscopy (OB-CEM)
The use of Optical Biopsies-OB (in the present case Confocal endomicroscopy-CEM) is limited due to
difficulties to interpret images. The OB-CEM are taken by endoscopists, not trained in microscopic morphology
which is the domain of the surgical pathology. To gain diagnostic confidence the endoscopists
could consult the images to a pathologist or could use the technique proposed in the paper. That is, to search
for similar images on Internet to compare the diagnosis.
The present paper is a positioning paper of how to build a CEM-image metadata to be used by the multimedia
standards ISO-15938-12:2008 and ISO-24800-3 in order to search on line using a “query by image”.
Metadata semantics based on Kudo colorectal crypt architecture was used for annotation or automatic image
extraction. The training set was composed of 25 OB-CEM chromo-colonoscopy images taken with a
FICE (Fujinon Intelligent Chromoendoscopy). Those parameters were, whenever possible, automatically
extracted from the image and included in the metadata for image mining. Future developments will annotate
histological images is such a way that the query could also retrieve the histological image.Postprint (published version
Query by image medical training: optical biopsy with confocal endoscopy (OB-CEM)
The use of Optical Biopsies-OB (in the present case Confocal endomicroscopy-CEM) is limited due to
difficulties to interpret images. The OB-CEM are taken by endoscopists, not trained in microscopic morphology
which is the domain of the surgical pathology. To gain diagnostic confidence the endoscopists
could consult the images to a pathologist or could use the technique proposed in the paper. That is, to search
for similar images on Internet to compare the diagnosis.
The present paper is a positioning paper of how to build a CEM-image metadata to be used by the multimedia
standards ISO-15938-12:2008 and ISO-24800-3 in order to search on line using a “query by image”.
Metadata semantics based on Kudo colorectal crypt architecture was used for annotation or automatic image
extraction. The training set was composed of 25 OB-CEM chromo-colonoscopy images taken with a
FICE (Fujinon Intelligent Chromoendoscopy). Those parameters were, whenever possible, automatically
extracted from the image and included in the metadata for image mining. Future developments will annotate
histological images is such a way that the query could also retrieve the histological image
Query by image medical training: optical biopsy with confocal endoscopy (OB-CEM)
The use of Optical Biopsies-OB (in the present case Confocal endomicroscopy-CEM) is limited due to
difficulties to interpret images. The OB-CEM are taken by endoscopists, not trained in microscopic morphology
which is the domain of the surgical pathology. To gain diagnostic confidence the endoscopists
could consult the images to a pathologist or could use the technique proposed in the paper. That is, to search
for similar images on Internet to compare the diagnosis.
The present paper is a positioning paper of how to build a CEM-image metadata to be used by the multimedia
standards ISO-15938-12:2008 and ISO-24800-3 in order to search on line using a “query by image”.
Metadata semantics based on Kudo colorectal crypt architecture was used for annotation or automatic image
extraction. The training set was composed of 25 OB-CEM chromo-colonoscopy images taken with a
FICE (Fujinon Intelligent Chromoendoscopy). Those parameters were, whenever possible, automatically
extracted from the image and included in the metadata for image mining. Future developments will annotate
histological images is such a way that the query could also retrieve the histological image