Application of spectrum analysis and neural-network classification to imaging for targeting and monitoring treatment of prostate cancer

被引:0
|
作者
Feleppa, EJ [1 ]
Ketterling, JA [1 ]
Kalisz, A [1 ]
Urban, S [1 ]
Schiff, PB [1 ]
Ennis, RD [1 ]
Wuu, CS [1 ]
Porter, CR [1 ]
Fair, WR [1 ]
Gillespie, JW [1 ]
机构
[1] Riverside Res Inst, New York, NY USA
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中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Conventional B-mode ultrasound is the standard means of imaging the prostate for guiding prostate biopsies and planning brachytherapy of prostate cancer. Yet no imaging modality, including B-mode images, reliably shows cancerous lesions of the prostate. Tissue-typing imaging based on spectrum analysis of ultrasonic radio-frequency (RF) echo signals may be able to overcome the limitations of conventional imaging modalities for visualizing prostate tumors. Such tissue typing utilizes neural-networks, to classify tissue based on spectral-parameter and clinical-variable values. Tissue-type images based on these methods are intended to improve guidance of prostate biopsies and targeting of radiotherapy of prostate cancer. Two-dimensional images have been imported into instrumentation for real-time biopsy guidance and into commercial dose-planning software for brachytherapy planning. Three-dimensional renderings show locations and volumes of cancer foci.
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收藏
页码:1269 / 1272
页数:4
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