Rathi et al., 2022 - Google Patents
Feasibility of quantitative tissue characterization using novel parameters extracted from photoacoustic power spectrum considering multiple absorbersRathi et al., 2022
- Document ID
- 8750409368019447149
- Author
- Rathi N
- Sinha S
- Chinni B
- Dogra V
- Rao N
- Publication year
- Publication venue
- Ultrasonic Imaging
External Links
Snippet
Frequency domain analysis of radio frequency signal is performed to differentiate between different tissue categories in terms of spectral parameters. However, due to complex relationship between the absorber size and spectral parameters, they cannot be used for …
- 239000006096 absorbing agent 0 title abstract description 138
Classifications
-
- 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
-
- 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
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7253—Details of waveform analysis characterised by using transforms
-
- 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
- G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
- G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
- G01N21/65—Raman scattering
- G01N2021/653—Coherent methods [CARS]
-
- 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
- A61B5/0093—Detecting, measuring or recording by applying one single type of energy and measuring its conversion into another type of energy
- A61B5/0095—Detecting, measuring or recording by applying one single type of energy and measuring its conversion into another type of energy by applying light and detecting acoustic waves, i.e. photoacoustic measurements
-
- 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
-
- 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
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
-
- 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
- A61B5/41—Detecting, measuring or recording for evaluating the immune or lymphatic systems
- A61B5/414—Evaluating particular organs or parts of the immune or lymphatic systems
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| El-Shenawee et al. | Cancer detection in excised breast tumors using terahertz imaging and spectroscopy | |
| Kim et al. | Towards clinical photoacoustic and ultrasound imaging: probe improvement and real-time graphical user interface | |
| Van Dijk et al. | Recovery of absorption spectra from Fourier transform infrared (FT-IR) microspectroscopic measurements of intact spheres | |
| Pu et al. | Determination of optical coefficients and fractal dimensional parameters of cancerous and normal prostate tissues | |
| Amidi et al. | Classification of human ovarian cancer using functional, spectral, and imaging features obtained from in vivo photoacoustic imaging | |
| Wan et al. | Effects of fatty infiltration in human livers on the backscattered statistics of ultrasound imaging | |
| Parker et al. | Burr, Lomax, Pareto, and logistic distributions from ultrasound speckle | |
| Chi et al. | An improved background-correction algorithm for Raman spectroscopy based on the wavelet transform | |
| Zhou et al. | Liver fibrosis assessment using radiomics of ultrasound homodyned-K imaging based on the artificial neural network estimator | |
| Langton et al. | A deconvolution method for deriving the transit time spectrum for ultrasound propagation through cancellous bone replica models | |
| Muleki-Seya et al. | Analysis of two quantitative ultrasound approaches | |
| DiSpirito III et al. | Sounding out the hidden data: a concise review of deep learning in photoacoustic imaging | |
| Li et al. | Utilizing spatial and spectral features of photoacoustic imaging for ovarian cancer detection and diagnosis | |
| Liu et al. | Spectral-based quantitative ultrasound imaging processing techniques: comparisons of RF versus IQ approaches | |
| Samimi et al. | Lower bound on estimation variance of the ultrasonic attenuation coefficient using the spectral-difference reference-phantom method | |
| Nordberg et al. | Effective scatterer diameter estimates for broad scatterer size distributions | |
| Zhang et al. | Identification of different types of tumors based on photoacoustic spectral analysis: preclinical feasibility studies on skin tumors | |
| Biswas et al. | Quantitative differentiation of pneumonia from normal lungs: Diagnostic assessment using photoacoustic spectral response | |
| Rich et al. | Performance characteristics of photoacoustic imaging probes with varying frequencies and light-delivery schemes | |
| Santoso et al. | A Geometric Model of Ultrasound Backscatter to Describe Microstructural Anisotropy of Tissue | |
| Rathi et al. | Computation of photoacoustic absorber size from deconvolved photoacoustic signal using estimated system impulse response | |
| Rubert et al. | Mean scatterer spacing estimation in normal and thermally coagulated ex vivo bovine liver | |
| Rathi et al. | Feasibility of quantitative tissue characterization using novel parameters extracted from photoacoustic power spectrum considering multiple absorbers | |
| Meng et al. | Compressed sensing with a Gaussian scale mixture model for limited view photoacoustic computed tomography in vivo | |
| Vardaki et al. | Determination of depth in transmission Raman spectroscopy in turbid media using a beam enhancing element |