Rey-Barroso et al., 2019 - Google Patents
Morphological study of skin cancer lesions through a 3D scanner based on fringe projection and machine learningRey-Barroso et al., 2019
View HTML- Document ID
- 2075964169401892908
- Author
- Rey-Barroso L
- Burgos-Fernández F
- Ares M
- Royo S
- Puig S
- Malvehy J
- Pellacani G
- Espinar D
- Sicilia N
- Ricart M
- Publication year
- Publication venue
- Biomedical optics express
External Links
Snippet
The effective and non-invasive diagnosis of skin cancer is a hot topic, since biopsy is a costly and time-consuming surgical procedure. As skin relief is an important biophysical feature that can be difficult to perceive with the naked eye and by touch, we developed a …
- 230000003902 lesions 0 title abstract description 30
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/47—Scattering, i.e. diffuse reflection
- G01N21/4795—Scattering, i.e. diffuse reflection spatially resolved investigating of object in scattering medium
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
- A61B5/44—Detecting, measuring or recording for evaluating the integumentary system, e.g. skin, hair or nails
- A61B5/441—Skin evaluation, e.g. for skin disorder diagnosis
- A61B5/444—Evaluating skin marks, e.g. mole, nevi, tumour, scar
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical means
- G01B11/24—Measuring arrangements characterised by the use of optical means for measuring contours or curvatures
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
- A61B5/0059—Detecting, measuring or recording for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
- A61B5/0062—Arrangements for scanning
- A61B5/0064—Body surface scanning
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
- A61B5/0059—Detecting, measuring or recording for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
- A61B5/0082—Detecting, measuring or recording for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence adapted for particular medical purposes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Rey-Barroso et al. | Optical technologies for the improvement of skin cancer diagnosis: a review | |
Heist et al. | 5D hyperspectral imaging: fast and accurate measurement of surface shape and spectral characteristics using structured light | |
Panigrahi et al. | Machine learning approach for rapid and accurate estimation of optical properties using spatial frequency domain imaging | |
Chang et al. | Multimodal sensor system for pressure ulcer wound assessment and care | |
CN103959040B (en) | Optical coherence tomography system is attached on smart mobile phone | |
Tilbury et al. | Second harmonic generation microscopy analysis of extracellular matrix changes in human idiopathic pulmonary fibrosis | |
Majeed et al. | Quantifying collagen fiber orientation in breast cancer using quantitative phase imaging | |
Nandy et al. | Characterizing optical properties and spatial heterogeneity of human ovarian tissue using spatial frequency domain imaging | |
Adler et al. | Comparison of three-dimensional optical coherence tomography and high resolution photography for art conservation studies | |
Li et al. | Automated quantification of microstructural dimensions of the human kidney using optical coherence tomography (OCT) | |
Delpueyo et al. | Multispectral imaging system based on light-emitting diodes for the detection of melanomas and basal cell carcinomas: a pilot study | |
Rey-Barroso et al. | Morphological study of skin cancer lesions through a 3D scanner based on fringe projection and machine learning | |
Sekulska-Nalewajko et al. | A method for the assessment of textile pilling tendency using optical coherence tomography | |
Nandy et al. | Classification and analysis of human ovarian tissue using full field optical coherence tomography | |
Dubey et al. | Low coherence quantitative phase microscopy with machine learning model and Raman spectroscopy for the study of breast cancer cells and their classification | |
Ilișanu et al. | Multispectral imaging for skin diseases assessment—state of the art and perspectives | |
Fitzgerald et al. | Co-registered combined OCT and THz imaging to extract depth and refractive index of a tissue-equivalent test object | |
Krishnaswamy et al. | Structured light scatteroscopy | |
Wang et al. | Deep learning-based optical coherence tomography image analysis of human brain cancer | |
Kim et al. | Data-driven imaging of tissue inflammation using RGB-based hyperspectral reconstruction toward personal monitoring of dermatologic health | |
Basevi et al. | Simultaneous multiple view high resolution surface geometry acquisition using structured light and mirrors | |
Jung et al. | Deep learning-based optical approach for skin analysis of melanin and hemoglobin distribution | |
Wu et al. | Optical coherence elastography based on inverse compositional Gauss-Newton digital volume correlation with second-order shape function | |
Harms et al. | En-face full-field optical coherence tomography for fast and efficient fingerprints acquisition | |
Häffner et al. | Density-dependent determination of scattering properties of pharmaceutical tablets using coherent backscattering spectroscopy |