Research Publications

Permanent URI for this communityhttps://rda.sliit.lk/handle/123456789/4194

This main community comprises five sub-communities, each representing the academic contribution made by SLIIT-affiliated personnel.

Browse

Search Results

Now showing 1 - 3 of 3
  • Thumbnail Image
    PublicationOpen Access
    Pneumonia Detection and Lung Disease Assessment from Chest X-rays: Developing A Diagnostic Support System
    (SLIIT, Faculty of Engineering, 2025-01) Jayawardena, C.A; Wedasingha, N; Kolambage, N; Perera, S
    This research, dedicated to developing an accurate and efficient pneumonia detection system from Chest X-Ray images, highlights the significance of automated tools in enhancing healthcare diagnostics. Its significance lies in the fact that pneumonia is a prevalent respiratory condition that requires timely and accurate diagnosis for effective medical intervention. The project's objective was to make use of convolutional neural networks and image analyses to create an automated diagnostic tool that could assist healthcare professionals in identifying pneumonia with precision and efficiency. To achieve this, the system initially made use of two custom deep learning architectures but ultimately used a pretrained CheXNet-based model, developed by using transfer learning. This choice was made by considering CheXNet’s proven performance in identifying pneumonia and other pulmonary conditions. The project's results proved promising, with the CheXNet-based model achieving high diagnostic accuracy and providing valuable insights into the presence of pneumonia. The system's architecture, using deep learning and the use of DICOM images, demonstrated its effectiveness in improving the accuracy and efficiency of pneumonia diagnosis. Based on the results, this paper further demonstrates a web-based application for interaction with the system. Additionally, it provides information on the work that could be done in the future. Thus, this research contributes to the growing field of medical image analysis and highlights the significance of automated tools in enhancing healthcare diagnostics. The project's outcomes are meant to pave the way for more efficient and accessible methods for pneumonia detection, ultimately benefiting both healthcare providers and patients.
  • Thumbnail Image
    PublicationOpen Access
    Picture Archiving and Communications System (PACS) for Government Hospitals in Sri Lanka
    (eHealth Asia 2015At: Colombo, 2015-10) Amarathunga, S. D. D; Jayasundara, P. P. A. S; Somaweera, E. G. P. P; Weerasena, P. D. C; Pulasinghe, K; Samarathunga, S. A. U. S
    In this modern world, Healthcare medical imaging system plays and important and central role in critical factor for the quality of diagnostic and treatments. Picture archiving and Communication System (PACS) is the backbone of the analysis of medical images as it is well adapt with several standards such as DICOM and HL7.
  • Thumbnail Image
    PublicationOpen Access
    Web Based Voice Controlled Advanced PACS to Diagnose Lungs Cancer and Related Anomalies
    (www.ijisrt.com, 2019-10) Ratnasingam, T; Sayanthan, A; Velummylum, E. S; Archchana, K; Pulasinghe, K
    - PACS (picture archiving and communication system) is a medicinal imaging technology that is utilized basically in medicinal services associations to safely store and dissect carefully transmit electronic pictures. PACS a needed asset in contemporary hospitals, has demonstrated its key position in the department of radiology for archiving and collecting medical images, followed by its inclusion with the department of radiology. In this paper we have included work 3D displaying of DICOM pictures, calculation of segmented cancer part with fine calculations, voice recognition for a program to get and translate correspondence or to comprehend and complete spoken directions, and forecast of malignancy utilizing examinations of cancer symptoms.