Research Group Coordinator
Dr Srinivasa Rao Sirasanagandla
Email: srinivasa@squ.edu.om
Overview:
Cadavers are traditionally used to study the basic structure and variations of the body. Conducting such research is clinically important to understand the disease process, planning the surgeries and treatment, developing a medical device, etc. The number of publications from cadaveric research has drastically reduced in recent years due to a lack of resources, such as the as the availability of cadavers, and ethical concerns in some parts of the world. Due to these reasons, researchers are currently relying on imaging data to conduct research to explore these areas. Radiological anatomy research is advantageous due to the availability of vast data and accessibility to different imaging modalities, including X-ray, CT, MRI, and ultrasound. These imaging resources provide various opportunities to explore the morphology and clinical anatomy research. Forensic medicine plays a crucial role in addressing legal issues that arise in both civil and criminal law contexts. Forensic anthropologists can identify the human skeletal remains based on the skeletal variations between the individuals. Knowing population-specific biological profile is essentially important for the forensic anthropology investigations.
The AI models are known to perform well with more data, and as we progress with the initial version, there will be scalability options to refine the model’s accuracy. The AI interface is designed to be user-friendly. The model will have a user-friendly interface using the Gradio API, which will give the participant a seamless and intuitive experience of interacting with the AI model. In recent years, the focus on radiological anatomy research has grown enormously. Although AI-powered applications, such as MONAI Label, have already been developed to assist in labeling and annotating radiological images, significantly reducing annotation efforts, there are still gaps in the integration of personalized AI models specifically tailored for radiological anatomy education. To address these challenges, there is a need to develop AI-based models integrating the AI power to facilitate an interactive, reliable, and immersive learning experience for radiological images.
The main aim of establishing our research group is to conduct innovative research in radiological anatomy in addition to the basic anatomy research. The main strength of our team is having members from both the radiology and anatomy disciplines and having an international collaboration. Additionally, the research group will involve the medical undergraduates of SQU, Oman Medical Specialty Board residents, and health science students from various institutions in Oman for conducting the research activities.
Our research group comply with international and local regulations on data privacy, including the General Data Protection Regulation (GDPR) for handling medical images and health data. Prior Ethical approval will be obtained for all the studies conducted from the Institutional Medical Research Ethics Committee (MREC) at SQU. All study activities, including data collection, processing, and analysis, will be conducted in accordance with the highest ethical standards to ensure the protection of patient rights and confidentiality.
The outcomes of our group research activities have great potential to achieve the goals of Oman Vision 2040. The innovative technology that we develop in our focused research fields will increase the impact of the SQU globally.