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Artificial intelligence-based early warning method for BPH (benign prostatic hyperplasia) bipolar prostatectomy

A technology of benign prostatic hyperplasia and artificial intelligence, applied in the early warning field of bipolar electrosurgical resection of benign prostatic hyperplasia, can solve problems such as excessive cutting, achieve the effect of improving the success rate and reducing the risk of excessive cutting of the prostate capsule

Inactive Publication Date: 2019-06-18
WUHAN UNIV
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AI Technical Summary

Problems solved by technology

However, in the cutting process, especially for young doctors with little experience in surgery, there is a potential for excessive cutting, which is a great threat to patients

Method used

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  • Artificial intelligence-based early warning method for BPH (benign prostatic hyperplasia) bipolar prostatectomy
  • Artificial intelligence-based early warning method for BPH (benign prostatic hyperplasia) bipolar prostatectomy
  • Artificial intelligence-based early warning method for BPH (benign prostatic hyperplasia) bipolar prostatectomy

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Embodiment Construction

[0026] In order to better understand the above-mentioned technical solution, the above-mentioned technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0027] The invention provides an artificial intelligence-based early warning method for bipolar electroresection of benign prostatic hyperplasia, which mainly includes the following steps: designing and constructing a squeezenet network; using authoritative data to make a data set in VOC format; importing the squeezenet network and data set into the TensorFlow framework , use the data set to train the squeezenet network to generate an early warning model; verify the model and data set on the PC side, evaluate the accuracy and feasibility of the model and data set, and then input the medical image of the resection of prostate hyperplasia to realize the prostate package Classification and identification of membranous tissue, providing surgical warni...

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Abstract

The invention belongs to the technical field of surgery assisting, and discloses an artificial intelligence-based early warning method for BPH (benign prostatic hyperplasia) bipolar prostatectomy. Themethod comprises the following steps: constructing a squeezenet network; acquiring data and establishing a data set; importing the squeezenet network and the data set into the TensorFlow framework, and using the data set to train the squeezenet network to generate an early warning model; inputting a medical image; calibrating the capsule position in the medical image according to the early warning model. Doctors can be assisted to perform judgment more accurately and rapidly, the risk of excessive prostate capsule incision caused by lack of operation experience of the surgery doctors is reduced, and the success rate of surgery is increased.

Description

technical field [0001] The invention relates to the technical field of auxiliary surgery, in particular to an artificial intelligence-based early warning method for bipolar electroresection of benign prostatic hyperplasia. Background technique [0002] Prostatic hyperplasia, often called benign prostatic hyperplasia, is one of the common diseases of middle-aged and elderly men, and its incidence is increasing with the aging of the global population. The incidence of benign prostatic hyperplasia increases with age, but there may not be clinical symptoms when there are hyperplasia lesions. Most patients will experience increased symptoms such as dysuria with age. The danger of benign prostatic hyperplasia lies in the pathophysiological changes caused by lower urinary tract obstruction, and the pathology varies greatly among individuals. Surgery is still an important treatment for benign prostatic hyperplasia, which is suitable for patients with moderate or severe prostatic hy...

Claims

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Application Information

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IPC IPC(8): A61B18/12A61B90/00
Inventor 郭洋左齐茹仪李佳
Owner WUHAN UNIV
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