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Advanced Medical AI Technology

ENT Insight

Advanced AI-Powered Medical Imaging Solution for ENT Clinical Environments

ENT Domain Overview

Ear, Nose & Throat Medicine

ENT Medical Imaging

Over the past few decades, the healthcare sector has adopted software solutions for managing patient records and medical imaging, significantly improving diagnostic processes. More recently, the integration of artificial intelligence (AI) into medical imaging has enhanced the identification of abnormalities, particularly through deep learning (DL) models.

This has opened new possibilities for accurate and efficient diagnostics in various medical fields. One such field is the Ear, Nose, and Throat (E.N.T.) domain, which handles a wide range of conditions affecting these areas.

Ear

Specializes in diagnosing and treating conditions affecting the ear, including hearing loss, ear infections, balance disorders, tinnitus, and congenital disorders.

Nose

Focuses on nasal and sinus conditions including sinusitis, allergies, polyps, deviated septum, and other disorders affecting breathing and smell.

Throat

Addresses throat-related issues including voice disorders, swallowing difficulties, tonsillitis, pharyngitis, and detection of foreign objects.

AI in ENT Diagnostics

Artificial Intelligence is revolutionizing ENT diagnostics through:

  • Enhanced image analysis for detecting abnormalities in medical scans

  • Automated classification of ENT conditions with high accuracy

  • Reduced diagnostic time and improved patient outcomes

Deep Learning models are particularly effective for:

  • Analyzing complex patterns in medical images that may be missed by human eyes

  • Providing decision support for clinicians in challenging cases

  • Enabling early detection of conditions for better treatment outcomes

Medical Conditions We Address

Foreign Objects in Throat

Foreign Objects X-Ray

Animal bones (as food), metallic objects (safety pins, needles), and biomedical foreign objects are common foreign objects that can be identified in the throat area.

Foreign objects can be identified using lateral neck X-ray radiographs.

View Types

Sinusitis

Sinusitis X-Ray

Sinusitis is the inflammation of the sinus tissue, caused by infections or allergies.

It causes headaches, thick nasal mucus, a plugged nose, and facial pain.

View Severity Levels

Cholesteatoma

Cholesteatoma Image

Cholesteatoma is a destructive and expanding growth of keratinizing squamous epithelium in the middle ear and/or mastoid process.

Destroys middle ear bones (ossicles) and can grow through the skull base into the brain. Can be identified using otoscopic images.

View Stages

Pharyngitis

Pharyngitis Image

Pharyngitis is an inflammation of the pharynx, often caused by viral or bacterial infections.

Leading to symptoms like sore throat, difficulty swallowing, and swollen lymph nodes. High-resolution images of the throat are obtained to visualize inflammation, redness, and swelling.

View Stages

Research Gaps Identified

Lack of Software Solutions

In existing research, there was no consideration for creating comprehensive software solutions.

Outdated Methods

Existing research was somewhat outdated. There are new deep learning technologies that can be used for this line of work.

Limited Model Evaluation

Different types of models or state-of-the-art models were not considered in previous studies.

Research Problem & Solution

Research Question

How to create a Web/Mobile based software solution to be used in E.N.T clinical environment which can be used for identifying medical conditions from certain medical images?

Solution Demo

System Architecture & Methodology

System Architecture Diagram Open Image

System Overview

The system architecture diagram shows the overall design of the proposed medical imaging application, which includes four sub-modules for detecting and diagnosing Cholesteatoma, Sinusitis, Foreign Objects in the throat, and Pharyngitis.

It has two front-end interfaces: a web app built with NextJS and a mobile app built with Flutter. These allow doctors and radiologists to upload medical images, view reports, and access patient data.

Technical Implementation

Backend Architecture

NodeJS-based REST API with Flask server for deep learning analysis

AI Models

CNN models including ResNet50, VGG16, InceptionV3, and YOLO

Multi-Platform

Web and mobile interfaces for comprehensive accessibility

Project Milestones

1

Topic Assessment

Discussion on research Domain & Scope

Completed
2

Project Proposal

Initial research proposal and literature review

Completed
3

Progress Presentation 1

System design and initial implementation

Completed
4

Progress Presentation 2

90% Completion Of The Project

Completed
5

Final Report

Final Report Submission

Completed
6

Final Presentation

Complete system demonstration and evaluation

Completed

Timeline Of The Project

13 May 2024 0/100

Topic Assessment

Initial research and problem identification. Team formation and project scope definition.

5 July 2024 6/100

Project Proposal Presentation

Demonstrating the Project Proposal

23 Aug 2024 6/100

Proposal Submission

Proposal Draft Submission

5 Dec 2024 15/100

Progress Presentation

Presenting the 50% Progress of the Solution

5 Dec 2024 1/100

Checklist 1

Submitting the Github Repo

17 Mar 2025 1/100

Checklist 2

Submitting the Demonstration Video

18 Mar 2025 18/100

Progress Presentation 2

Demonstrating 90% Completed Project

20 Mar 2025 0/100

Research Paper

Submitting the Research Paper

11 Apr 2025 20/100

Final Reports

Submitting the Final Reports for Supervisor Evaluation

27 May 2025 20/100

Final Presentation & Viva

Final Presentation & Viva Session with Finalized Product presentation

27 May 2025 2/100

Static Website Demonstration

Demonstration of Static website with Project details

02 June 2025 10/100

Research Forum

Forum on Submitted Research Papers

Our Team

Pasan Baddewithana

Pasan Baddewithana

Student

it21247804@my.sliit.lk

Navod Fonseka

Navod Hansajith Fonseka

Student

it21156410@my.sliit.lk

Maneesh Prashantha

Maneesh Prashantha

Student

it21169908@my.sliit.lk

Nishadi Nawanjala

Nishadi Nawanjala

Student

it21156038@my.sliit.lk

Jenny Krishara

Jenny Krishara

Senior Lecturer

jenny.k@sliit.lk

Kanishka Yapa

Kanishka Yapa

Lecturer

kanishka.y@sliit.lk

Dr. Selvarajini Vettivelu

Dr. Selvarajini Vettivelu

E.N.T Consultant

Medical Advisor

Snapshots from the Field Visits

Explore our journey through these visual highlights captured during our field research and clinical observations.

Our Solution

Contact Us

Get in Touch

research@entinsight.com
+94 76 617 1525
SLIIT, New Kandy Road, Malabe, Sri Lanka

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