Machine-learning classification of non-melanoma skin cancers from image features obtained by optical coherence tomography.
about
A clinical instrument for combined raman spectroscopy-optical coherence tomography of skin cancers.Optical biopsy of epithelial cancers by optical coherence tomography (OCT).Pilot clinical study for quantitative spectral diagnosis of non-melanoma skin cancer.Clinical application of optical coherence tomography for the imaging of non-melanocytic cutaneous tumors: a pilot multi-modal studyOptical coherence tomography in the diagnosis of basal cell carcinoma.A novel imaging approach to periocular basal cell carcinoma: in vivo optical coherence tomography and histological correlatesOptical coherence tomography-current technology and applications in clinical and biomedical research.Optical coherence tomography in dermatology: technical and clinical aspects.Optical techniques for the noninvasive diagnosis of skin cancer.Systematic review of optical coherence tomography usage in the diagnosis and management of basal cell carcinoma.Classification of basal cell carcinoma in human skin using machine learning and quantitative features captured by polarization sensitive optical coherence tomography.Automated identification of basal cell carcinoma by polarization-sensitive optical coherence tomography.The sensitivity and specificity of optical coherence tomography for the assisted diagnosis of nonpigmented basal cell carcinoma: an observational study.How histological features of basal cell carcinomas influence image quality in optical coherence tomography.Optical coherence tomography of actinic keratoses and basal cell carcinomas - differentiation by quantification of signal intensity and layer thickness.Morphology of basal cell carcinoma in high definition optical coherence tomography: en-face and slice imaging mode, and comparison with histology.Histological correlates of optical coherence tomography in non-melanoma skin cancer.Actinic keratosis in the en-face and slice imaging mode of high-definition optical coherence tomography and comparison with histology.Universal in vivo Textural Model for Human Skin based on Optical Coherence Tomograms.Dimension reduction technique using a multilayered descriptor for high-precision classification of ovarian cancer tissue using optical coherence tomography: a feasibility study.Noninvasive optical spectroscopy for identification of non-melanoma skin cancer: Pilot study.Automatic identification of parathyroid in optical coherence tomography images.Three-phase general border detection method for dermoscopy images using non-uniform illumination correction.
P2860
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P2860
Machine-learning classification of non-melanoma skin cancers from image features obtained by optical coherence tomography.
description
2008 nî lūn-bûn
@nan
2008年の論文
@ja
2008年論文
@yue
2008年論文
@zh-hant
2008年論文
@zh-hk
2008年論文
@zh-mo
2008年論文
@zh-tw
2008年论文
@wuu
2008年论文
@zh
2008年论文
@zh-cn
name
Machine-learning classificatio ...... optical coherence tomography.
@en
Machine-learning classificatio ...... optical coherence tomography.
@nl
type
label
Machine-learning classificatio ...... optical coherence tomography.
@en
Machine-learning classificatio ...... optical coherence tomography.
@nl
prefLabel
Machine-learning classificatio ...... optical coherence tomography.
@en
Machine-learning classificatio ...... optical coherence tomography.
@nl
P2093
P1476
Machine-learning classificatio ...... y optical coherence tomography
@en
P2093
Andreas Tycho
Mette Mogensen
Peter Bjerring
P304
P356
10.1111/J.1600-0846.2008.00304.X
P577
2008-08-01T00:00:00Z