UreteroPelvic Junction Obstruction(UPJO)is a common hydronephrosis disease in children that can result in an even progressive loss of renal function.Ultrasonography is an economical,radiationless,noninvasive,and high ...UreteroPelvic Junction Obstruction(UPJO)is a common hydronephrosis disease in children that can result in an even progressive loss of renal function.Ultrasonography is an economical,radiationless,noninvasive,and high noise preliminary diagnostic step for UPJO.Artificial intelligence has been widely applied to medical fields and can greatly assist doctors'diagnostic abilities.The demand for a highly secure network environment in transferring electronic medical data online,therefore,has led to the development of blockchain technology.In this study,we built and tested a framework that integrates a deep learning diagnosis model with blockchain technology.Our diagnosis model is a combination of an attention-based pyramid semantic segmentation network and a discrete wavelet transformation-processed residual classification network.We also compared the performance between benchmark models and our models.Our diagnosis model outperformed benchmarks on the segmentation task and classification task with MloU=87.93,MPA=93.52,and accuracy=91.77%.For the blockchain system,we applied the InterPlanetary File System protocol to build a secure and private sharing environment.This framework can automatically grade the severity of UPJO using ultrasound images,guarantee secure medical data sharing,assist in doctors'diagnostic ability,relieve patients'burden,and provide technical support for future federated learning and linkage of the Internet of Medical Things(loMT).展开更多
Dear Editor,Lipoblastomatosis is a rare benign soft tissue tumor arising from the white fetal-embryonal adipose tissue（Choi et al.,2013）.Since the distinction of lipoblastomatosis from lipoblastma was reported by Ve...Dear Editor,Lipoblastomatosis is a rare benign soft tissue tumor arising from the white fetal-embryonal adipose tissue（Choi et al.,2013）.Since the distinction of lipoblastomatosis from lipoblastma was reported by Vellios et al.,there are only a few studies,and the incidence rate is approximately3.5/1,000,000.展开更多
基金This study was supported by the National Key R&D Program of China(No.2020YFB2104402).
文摘UreteroPelvic Junction Obstruction(UPJO)is a common hydronephrosis disease in children that can result in an even progressive loss of renal function.Ultrasonography is an economical,radiationless,noninvasive,and high noise preliminary diagnostic step for UPJO.Artificial intelligence has been widely applied to medical fields and can greatly assist doctors'diagnostic abilities.The demand for a highly secure network environment in transferring electronic medical data online,therefore,has led to the development of blockchain technology.In this study,we built and tested a framework that integrates a deep learning diagnosis model with blockchain technology.Our diagnosis model is a combination of an attention-based pyramid semantic segmentation network and a discrete wavelet transformation-processed residual classification network.We also compared the performance between benchmark models and our models.Our diagnosis model outperformed benchmarks on the segmentation task and classification task with MloU=87.93,MPA=93.52,and accuracy=91.77%.For the blockchain system,we applied the InterPlanetary File System protocol to build a secure and private sharing environment.This framework can automatically grade the severity of UPJO using ultrasound images,guarantee secure medical data sharing,assist in doctors'diagnostic ability,relieve patients'burden,and provide technical support for future federated learning and linkage of the Internet of Medical Things(loMT).
文摘Dear Editor,Lipoblastomatosis is a rare benign soft tissue tumor arising from the white fetal-embryonal adipose tissue（Choi et al.,2013）.Since the distinction of lipoblastomatosis from lipoblastma was reported by Vellios et al.,there are only a few studies,and the incidence rate is approximately3.5/1,000,000.
