Deep learning-based glomerular segmental sclerosis degree determination method, computer equipment and computer readable storage medium

• Main Authors: WANG TAIPING, ZHANG MINFEI
• Format: Patent
• Language: Chinese; English
• Published: 01.03.2022
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; HANDLING RECORD CARRIERS; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL; PHYSICS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS

The invention discloses a glomerular segmental sclerosis degree determination method based on deep learning, computer equipment and a computer readable storage medium, the method can be used for determining glomerular segmental sclerosis and the degree thereof, and an accurate basis is provided for subsequent diagnosis and treatment. According to the method, the average processing time of each picture is 4.768 * 10 <-7 > ms, and the accuracy rate of the method is 97% or above. The method provided by the invention can be used for solving the problems of poor accuracy and poor effectiveness of traditional image processing at present. 本发明公开了一种基于深度学习的肾小球节段性硬化程度确定方法、计算机设备及计算机可读存储介质，本发明的方法能够用于确定肾小球阶段性硬化及其程度，为后续的诊断与治疗提供了准确的依据。本发明中，平均每张图片处理用时4.768*10-7ms，本发明方法的准确率为97％以上。本申请所提出的方法，能够用于解决目前传统图像处理的准确性差与效性差的问题。