Spot diagnosis through medical imaging

As the name suggests, this is the most common application of diagnostic medical imaging. An image can tell us, at a glance, what exactly is wrong with the patient. Plain radiographs and CTs help detect fractures, cysts, tumors, and anomalies of the bone. One of the most promising areas of hea

Project Title

Spot diagnosis through medical imaging

Project Area of Specialization

Biomedical Engineering

Project Summary

As the name suggests, this is the most common application of diagnostic medical imaging. An image can tell us, at a glance, what exactly is wrong with the patient. Plain radiographs and CTs help detect fractures, cysts, tumors, and anomalies of the bone.

One of the most promising areas of health innovation is the application of artificial intelligence (AI) in medical imaging, including, but not limited to, image processing and interpretation.

Indeed, AI may find multiple applications, from image acquisition and processing to aided reporting, follow-up planning, data storage, data mining, and many others. Due to this wide range of applications, AI is expected to massively impact the radiologist’s daily life.

Project Objectives

Natural color image segmentation algorithm based on local information of an image will be implemented employing the recursive method using quad tree structure.

2. The perceptual color information will be computed statistically for each part under process of the image.

3. The design of the algorithm will be based on the pyramidal parallel processing approach to find out the spots

4. The statistically uniformity criteria investigated [8] will be adopted for the proposed image segmentation and color detection scheme. 

5. The existing methods and their performance will also be compared with our proposed method for natural image segmentation.

Project Implementation Method

The project will get one input image from sanner and then the image is preprocessed so taht the information extraction is possible. The spots of diseases are fond on the basis of various image processing algorithms. 

Medical imaging is often perceived to designate the set of techniques that noninvasively produce images of the internal aspect of the body. In this restricted sense, medical imaging can be seen as the solution of mathematical inverse problems. This means that cause (the properties of living tissue) is inferred from effect (the observed signal). In the case of medical ultrasound, the probe consists of ultrasonic pressure waves and echoes that go inside the tissue to show the internal structure. In the case of projectional radiography, the probe uses X-ray radiation, which is absorbed at different rates by different tissue types such as bone, muscle, and fat.

Benefits of the Project

• noninvasively and painlessly help to diagnose disease and monitor therapy;
• support medical and surgical treatment planning; and
• guide medical personnel as they insert catheters, stents, or other devices inside the body, treat tumors, or remove blood clots or other blockages.

Technical Details of Final Deliverable

Our project is the process of identifying a spot of  disease or illness based on a thorough examination of the patient. Unfortunately, most diseases and conditions affect areas of the body that are not normally visible to the naked eye.  our project diagnostic medical imaging can aid in diagnosis by allowing us to visualize any abnormalities that might exist within the body. For instance, in a patient who has sustained a trauma, medical imaging can tell us if any bones are broken or dislocated.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Medical

Other Industries

IT

Core Technology

Artificial Intelligence(AI)

Other Technologies

Shared Economy, Clean Tech

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

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