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shihao80's Projects

image-registration icon image-registration

A MATLAB library/toolbox providing access to image registration suitable for use with medical images.

indoorpos icon indoorpos

这是一个采用蓝牙4.0--iBeacon技术的室内定位服务端程序。

jbpm icon jbpm

a Business Process Management (BPM) Suite

jeecg-boot icon jeecg-boot

一款基于代码生成器的JAVA快速开发平台!采用最新技术,前后端分离架构:SpringBoot 2.x,Ant Design&Vue,Mybatis-plus,Shiro,JWT。强大的代码生成器让前后端代码一键生成,无需写任何代码,绝对是全栈开发福音!! JeecgBoot的宗旨是提高UI能力的同时,降低前后分离的开发成本,JeecgBoot还独创在线开发模式,No代码概念,一系列在线智能开发:在线配置表单、在线配置报表、在线设计流程等等。

jeecg-cloud icon jeecg-cloud

基于Spring Boot 2.1.3、 Spring Cloud Greenwich.SR3 & Alibaba、 Shiro、JWT的 JAVA快速开发平台(Jeecg Boot的微服务版本,功能和底层代码,两边保持同步)

jeecg-uniapp icon jeecg-uniapp

JEECG BOOT APP移动解决方案,采用Uniapp+ColorUI 框架,一份代码解决多终端适配(APP、小程序、H5)

koboldcom icon koboldcom

Serial port communication tool. 商业级 C#串口通讯通用框架

lh-ehr icon lh-ehr

LibreHealth EHR - Free Open Source Electronic Health Records

lidar-mos icon lidar-mos

Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data (RAL/IROS 2021)

linux icon linux

Linux kernel source tree for HiKey, HiKey960 and HiKey970

live-charts icon live-charts

Simple, flexible, interactive & powerful charts, maps and gauges for .Net

low-code-development-platform icon low-code-development-platform

Rintagi is the world's first fully open source low-code development platform. Build responsive mission-critical database systems with beautiful web interface. The only code you need to worry about is unique business rules on three tiers. Both High Productivity and High Control on a patented self-generating platform.

machinelearningformedicalimages icon machinelearningformedicalimages

Example code on how to apply machine learning methods to medical images. Contains code (python and python notebooks) and data (DICOM)

medical-image-classification-using-deep-learning icon medical-image-classification-using-deep-learning

Tumour is formed in human body by abnormal cell multiplication in the tissue. Early detection of tumors and classifying them to Benign and malignant tumours is important in order to prevent its further growth. MRI (Magnetic Resonance Imaging) is a medical imaging technique used by radiologists to study and analyse medical images. Doing critical analysis manually can create unnecessary delay and also the accuracy for the same will be very less due to human errors. The main objective of this project is to apply machine learning techniques to make systems capable enough to perform such critical analysis faster with higher accuracy and efficiency levels. This research work is been done on te existing architecture of convolution neural network which can identify the tumour from MRI image. The Convolution Neural Network was implemented using Keras and TensorFlow, accelerated by NVIDIA Tesla K40 GPU. Using REMBRANDT as the dataset for implementation, the Classification accuracy accuired for AlexNet and ZFNet are 63.56% and 84.42% respectively.

medpy icon medpy

Medical image processing in Python

meetup icon meetup

【❤️ 互联网最全大厂技术分享PPT 👍🏻 持续更新中!】🍻各大技术交流会、活动资料汇总 ,如 👉QCon👉全球运维技术大会 👉 GDG 👉 全球技术领导力峰会👉大前端大会👉架构师峰会👉敏捷开发DevOps👉OpenResty👉Elastic,欢迎 PR / Issues

metalpetal icon metalpetal

A GPU-accelerated image and video processing framework based on Metal.

mirtk icon mirtk

The Medical Image Registration ToolKit (MIRTK), the successor of the IRTK, contains common CMake build configuration files, core libraries, and basic command-line tools. Extension packages are hosted by the MIRTK GitHub group at

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