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10.1117/1.JBO.21.4.046006

http://scihub22266oqcxt.onion/10.1117/1.JBO.21.4.046006
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C4833884!4833884!27086690
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suck abstract from ncbi


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pmid27086690      J+Biomed+Opt 2016 ; 21 (4): ä
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  • Coregistered photoacoustic and ultrasound imaging and classification of ovarian cancer: ex vivo and in vivo studies #MMPMID27086690
  • Salehi HS; Li H; Merkulov A; Kumavor PD; Vavadi H; Sanders M; Kueck A; Brewer MA; Zhu Q
  • J Biomed Opt 2016[Apr]; 21 (4): ä PMID27086690show ga
  • Most ovarian cancers are diagnosed at advanced stages due to the lack of efficacious screening techniques. Photoacoustic tomography (PAT) has a potential to image tumor angiogenesis and detect early neovascular changes of the ovary. We have developed a coregistered PAT and ultrasound (US) prototype system for real-time assessment of ovarian masses. Features extracted from PAT and US angular beams, envelopes, and images were input to a logistic classifier and a support vector machine (SVM) classifier to diagnose ovaries as benign or malignant. A total of 25 excised ovaries of 15 patients were studied and the logistic and SVM classifiers achieved sensitivities of 70.4 and 87.7%, and specificities of 95.6 and 97.9%, respectively. Furthermore, the ovaries of two patients were noninvasively imaged using the PAT/US system before surgical excision. By using five significant features and the logistic classifier, 12 out of 14 images (86% sensitivity) from a malignant ovarian mass and all 17 images (100% specificity) from a benign mass were accurately classified; the SVM correctly classified 10 out of 14 malignant images (71% sensitivity) and all 17 benign images (100% specificity). These initial results demonstrate the clinical potential of the PAT/US technique for ovarian cancer diagnosis.
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