High-Level Project Summary
We have made a project on: “Automated Renal Cyst Detection and Segmentation Using Ultrasound Images”.Renal cyst is the most common lesion of kidneys.Our challenge is to detect and segment the renal cysts using Ultrasound Images.We have developed this projects in Python3 on a standard computer.The steps are given below:1. Image Pre-processing: In this step we have used various kinds of filters . We used Non local mean filter for image denoising, Gabor filter for edge preservation and Histogram equalization for contrast enhancement.2.Image processing( Detection and Segmentation): For detection, we used Blob detection technique. For segmentation we used K-mean & Watershed segmentation.
Link to Project "Demo"
Link to Final Project
Detailed Project Description
In today’s world the world need more technology. Image processing is one of the greatest sector in today’s world. This sector has many spheres to develope. Medical imaging is one of them. The name of our project is “ Automated Renal Cyst Detection and Segmentation Using Ultrasound Images”. This project describes a system which can detect and segment renal cysts using Ultrasound images
The process is described below:
Collect the 2D Ultrasound images of renal cyst affected kidneys of patients.
Image preprocessing: Use some filters for special purposes. We applied Non local mean filter for Image denoising, Gabor filter for Edge preservation and Histogram Equalization for Contrast Enhancement.
Image processing : In this step the main task of detection and segmentation is started.
Renal Cyst detection: We applied Blob Detection technique to Detect renal cysts .
Renal Cyst Segmentation : We applied Watershed Segmentation technique to Segment renal cysts .
Software & Hardware: Our project was implemented in Python3 on a standard computer
Space Agency Data
We have used data from google.com because we couldn't find any data i space agency related to our project.
Hackathon Journey
I want to thank all the co-ordinator and mentors. We are really glad to have a oppurtunity like Hackathon. We learned many things through this journey.
References
- data-www.google.com
- project: github.com
- Software: Python3
- Windows: Windows 10
- Hardware: Standard computer