2010
DOI: 10.1364/boe.2.000058
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Contrast improvement of terahertz images of thin histopathologic sections

Abstract: We present terahertz images of 10 μm thick histopathologic sections obtained in reflection geometry with a time-domain spectrometer, and demonstrate improved contrast for sections measured in paraffin with water. Automated segmentation is applied to the complex refractive index data to generate clustered terahertz images distinguishing cancer from healthy tissues. The degree of classification of pixels is then evaluated using registered visible microscope images. Principal component analysis and propagation si… Show more

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Cited by 18 publications
(14 citation statements)
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“…4 However, several classification methods have been applied to FFPE tissue applications and/ or spectroscopy of tissues, including wavelet transformation for osteosarcoma, 22 orthogonal signal correction and fuzzy rulebending expert system for cervical cancer, 23 multispectral classification of FFPE basal cell carcinoma, 24 and PCA for potentially malignant skin nevi 25 and FFPE liver cancer. 26,27 This work investigates a Bayesian mixture model utilizing a Markov chain Monte Carlo (MCMC) scheme for THz image classification of both fresh and FFPE murine breast tumors. 28 This work is different from the authors' previous work where they performed qualitative THz imaging and characterization of FFPE breast cancer tissue 8,9 as well as THz imaging and image processing of three-dimensional FFPE breast cancer tissue and characterization of carbon nanoparticles for THz contrast enhancement.…”
Section: Introductionmentioning
confidence: 99%
“…4 However, several classification methods have been applied to FFPE tissue applications and/ or spectroscopy of tissues, including wavelet transformation for osteosarcoma, 22 orthogonal signal correction and fuzzy rulebending expert system for cervical cancer, 23 multispectral classification of FFPE basal cell carcinoma, 24 and PCA for potentially malignant skin nevi 25 and FFPE liver cancer. 26,27 This work investigates a Bayesian mixture model utilizing a Markov chain Monte Carlo (MCMC) scheme for THz image classification of both fresh and FFPE murine breast tumors. 28 This work is different from the authors' previous work where they performed qualitative THz imaging and characterization of FFPE breast cancer tissue 8,9 as well as THz imaging and image processing of three-dimensional FFPE breast cancer tissue and characterization of carbon nanoparticles for THz contrast enhancement.…”
Section: Introductionmentioning
confidence: 99%
“…Similar to microwave radiation, and in contrast to X-rays, terahertz radiation can penetrate non-conducting materials, such as clothes, without causing ionising radiation damage. These properties make terahertz waves suitable for non-invasive biomedical imaging and cancer diagnosis 1 2 3 4 5 6 7 8 9 10 11 12 13 .…”
mentioning
confidence: 99%
“…For most cancers, confident diagnosis at an early stage is a challenging task, and several cross-checking tests are typically performed. Diseased or cancerous tissues contain more interstitial water than healthy tissues as a result of oedema or increased vascularity 3 , and the analysis of water content can be performed by measuring the absorption of terahertz radiation 1 2 3 4 5 6 7 8 9 10 11 12 . However, the absorption contrast is affected not only by the water content but also by the structural changes caused by cancer 4 .…”
mentioning
confidence: 99%
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