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

来源：

2001 IEEE ULTRASONICS SYMPOSIUM PROCEEDINGS, VOLS 1 AND 2 | 2001年

关键词：

D O I：

暂无

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.

引用

页码：1269 / 1272

页数：4

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