Faculty of Computing

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    PublicationEmbargo
    Segmentation and significance of herniation measurement using Lumbar Intervertebral Discs from the Axial View
    (IEEE, 2022-10-04) Siriwardhana, Y; Karunarathna, D; Ekanayake, I. U
    According to statistics, more than 60% of people suffer lower back pain at a certain time in their lives. Disc hernias are the most common cause of lower back pain, and the lumbar spine is responsible for more than 95% of all herniated discs. Generally, radiologists study the MRI during the clinical phase to detect a disc hernia. There could be several cases to evaluate, leaving the doctors to cogitate and envisage. Medical image segmentation aids in the diagnosis of spinal pathology, studying the anatomical structures, surgical procedures, and the evaluation of various treatments. However, manual segmentation of medical images necessitates a significant amount of time, effort, and discipline on the part of domain experts. This research study describes a framework that automates the segmentation of lumbar intervertebral discs using MRI images. Through this system, we can detect minor changes at the pixel level that are impossible to identify with the naked eye. We used convolutional neural networks with the UNet architecture to achieve the semantic segmentation process. The segmentations were evaluated using the Jacquard index and the dice coefficient.
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    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.