Medical Imaging

VISION :
To Create a Centre of Excellence in medical Imaging to provide solutions to various imaging challenges and innovative artificial intelligence imaging modalities in the diagnostic medical domain

MISSION:

To strengthen the knowledge up gradation of faculty members and students in respective domain.
To establish collaboration with various healthcare organizations such as Hospitals, Radiology centres, Research institutions and commercial industries.
To promote research activities such as funded and consultancy project execution, prototyping, intellectual property building and publications in the respective domain.

Research Activities:
To carry out advanced interdisciplinary research activities in the area Medical Imaging cater to the needs of the industry and society and using this as a general research facility to take up new research projects of healthcare sector.

Conducting Workshops, FDPs, Seminars, and design contest at regular intervals in order to kindle the awareness of faculty members and students.
Interacting with industrial experts in order to know the current state of affairs of medical imaging modalities.
Identifying the various problem statements in the current scenario so that projects and in turn quality publications will be done.
Regular discussions with people in the hospitals to know the requirement of them in order to propose suitable consultancy woks.
Establishing contacts with the funding agencies to devise suitable project proposals in the medical imaging domain.

Projects at Centre of Excellence in Medical Imaging
Project “AI tool for analyzing COVID condition in the test Chest X-Ray” is done at the centre during the pandemic situation and submitted and had discussion with Government sectors including ICMR

Project proposal submitted for UK innovation

Title of the proposed work	Objective	Carried by
Design and development of AI tool for analyzing COVID condition in the test Chest X-Ray	Identifying, Analysing and interpreting the COVID-19 condition and infection level within the lung segmented region will assist the physicians to facilitate better treatment to the infected patients and hence development of an efficient AI tool is the need of the hour in today’s scenario.	Dr.S.Rajkumar, Professor & Head/BME & Dr.V.Sapthagirivasan, Adjunct Fcaulty, BME

Project proposal submitted for National level funding agencies:

S.no	Title of the proposed work	Objective	Topic assigned to
1	3D volume generation from 2D C-arm images	To develop an algorithm to obtain 3-Dimensional reconstruction from 2-Dimensional image obtained from iso-centric C-Arm X ray machine.	Dr.S.Rajkumar Ms.R.Saidivya Faculty members/BME
2	Real-time Renal Stone Quantification and Classification System	Development of AI based dynamic stone quantification software tool for predicting the size and composition of kidney stones in real-time Ureteroscopy procedure	Dr.G.Nirmalapriya Mr. K.Sivakumar Ms.S.Sheela Faculty members/RIT
3	Conduct Preventive Analysis from Chest X-ray scan and Electronic Medical Record (EMR) Data	To automatically analyze the whole radiology (PA chest x-ray) scans and report all possible abnormalities present in the image in combination with EMR data with the aid of AI power such as Deep Learning.	Dr.K.Devaki, Co-HoD/CSE
4	Breast Mass Detection and Classification System for Digital Breast Tomosynthesis Images	To develop computer-aided detection system to identify masses presents in the digital breast Tomosynthesis volume data by extracting key image features and Deep Learning method.	Dr.T.Manikandan, Faculty/ECE
5	Human Performance Evaluation System	To develop a system which can measure human performances in working environments by analyzing Brain Dynamics for both physical (viz. cognitive, drowsiness) and mental (viz. excited, cheerful) conditions.	Dr.M.C.Jobin Christ, Ms.N.Padmasini Faculty members/BME

S.no	Title of the proposed work	Objective	Topic assigned to
1	Differentiation of benign and malignant breast tumor using Digital Breast Tomosynthesis	To differentiate the benign and malignant breast tissues with DBT using deep learning algorithms	Harini B G - lV year Malavika S - lV year Roshini B - lll year Raksidaa P - lll year Shrilekha T - lll year
2	Detection of cardiomegaly using machine learning and x rays	To detect the presence of cardiomegaly using x ray images using machine learning	Nithila J - III year Lithiga P - III year Jeswin Betcy - III year Prasanna - II year
3	VR based visualization of human body	Making a VR application in order to help medical professionals and medical students in medical schools to visualise the various anatomical areas and physiological regions in the human body, either by viewing the application or by superimposing the images on a 3D printed model for better visualisation.	S. Manikandan - 3rd year Arjun Bhattacharya - 3rd year R. Madhavan - 3rd year M. Madhav - 3rd year
4	Capsule Endoscopy	To detect ulcers,erosion and foreign body in Capsule endoscopic images using machine learning algorithm.	KRITHIKA GK- III yr DHANUSHA P -IIIyr HARINI CS -IIIyr CHANDRASEKAR –IIIyr
5	KL grading on Knee X-ray images	This is a deep learning model to automatically classify the given knee x-ray image into one of the four grades by KL grading system.	Saranya R- 3rd year Sandhiya N- 3rd year Shivani V- 3rd year Sairam V A- 3rd year
	"Urinary stone segmentation from Ureteroscopic image data" using machine learning algorithm	Using Ureteroscopic images,we are detecting the number of stones present using machine algorithm.	Keerthana KS -3rd year Jeffi Catherine -3rd year Malathi M- 3rd year Lakshmi Priya G- 3rd year

Training offered

National level Faculty Development Training Programme (FDTP) on "Image Analysis in Spatial Domain" during 23, 24 of November 2018 One day hands-on session on Embedded technologies.
Workshop on Recent Advancements and Research Scopes in Gastro-Intestinal Imaging Technologies” on 05.01.2019
Industry Oriented Hands-on Image Processing Training-2k19 for our students during 20-21 September 2019
Hands-on FTDP on Deep Learning in Medical Imaging Applications on 7th & 8th June 2019
Workshop on “Image Processing Using Open CV Hands-on Sessions” on 14.08.2021 and 21.08.2021
Guest Lecture on “Machine learning for Medical image Analysis” on 05.03.2022

Research Publications

S.Rajkumar, P.V.Rajaraman, Haree Shankar Meganathan, V. Sapthagirivasan, K.Tejaswinee, R.Ashwin, “COVID-Detect: A Deep Learning Approach for Classification of COVID-19 Pneumonia from Lung Segmented Chest X-rays” Biomedical Engineering: Applications, Basis and Communications 33 (02), 2150010 https://doi.org/10.4015/S1016237221500101
Two papers are in review process

Courses in curriculum

S.no.	Course code	Course name
1.	BM19741	Digital Image Processing Techniques
2.	BM19P71	Soft Computing methods
3.	BM19P86	Virtual Reality in Medical Applications
4	MX19201	Medical Imaging and Processing Techniques
5	MX19P25	Advanced Soft Computing

MoU’s Signed

Draft MoU submitted to M/S Aarthi Scans, Chennai.
Draft MoU submitted to M/S Medall, Chennai.
MoU is planning with M/S Sentinel Radiology Solutions
MoU is planning with Deepam Hospitals, Chennai