CT is the prime modality for diagnosis, treatment efficacy evaluation, and follow-up for brain and thorax pathologies which involves higher radiation and increases the risk of cancers. Optimization of radiation dose and contrast volume for CT Brain and Thorax examination is important for reducing the radiation and reducing the risk of Contrast-Induced Nephropathy (CIN) who requires follow-up contrast-enhanced CT. There are limited studies that evaluated the radiation dose and image quality of low dose and low contrast volume protocol for CT Brain and Thorax using the Deep Learning Based Reconstruction (DLR) algorithm. There are limited studies that compared the radiation dose and image quality for CT Brain and Thorax between iDose⁴ and Deep Learning Reconstruction (DLR) algorithm. This study consists of Phase I and Phase 2. Phase I of the study will be done for the patient who are referred for CT Brain Plain, CECT Brain, CECT Thorax and HRCT Thorax using standard dose settings. Qualitative analysis will be performed by two radiologists using five-pint likert scale for overall image quality, subjective noise and artefacts. The quantitative analysis will be performed by evaluating Signal to Noise Ratio, Contrast to Noise Ratio and Hounsfield Unit. The radiation dose information such as CTDIvol, Dose Length Product and Size Specific Dose Estimate will be noted from the console for each scans. The Phase II Low-dose protocol will be developed by scanning the Head and Body phantom with 100 kVp and different mAs settings (CT Brain Plain, CECT Brain 100-200 mAs, CECT Thorax and HRCT Thorax 20-40 mAs). For CT Brain, the optimum parameters were noted as 100 kVp and 200 mAs, which produced optimum image quality and reduced radiation dose. For CT Thorax, the optimum parameters were noted as 100 kVp and 40 mAs with optimum image quality and reduced radiation dose. Scanning will be performed using the low dose protocol in patients referred for CT Brain Plain, CECT Brain, CECT Thorax and HRCT Thorax (Table 2). The low-dose images will be reconstructed with deep learning reconstruction (DLR) algorithm . For CT Brain Plain, CECT Brain, CECT Thorax and HRCT Thorax the scan will be performed with a reduced volume of 30 ml and 40ml respectively. Qualitative analysis will be performed by two radiologists using five-pint likert scale for overall image quality, subjective noise and artefacts. The quantitative analysis will be performed by evaluating Signal to Noise Ratio, Contrast to Noise Ratio and Hounsfield Unit. The radiation dose information such as CTDIvol, Dose Length Product and Size Specific Dose Estimate will be noted from the console for each scans. The study is directly beneficial as it aims to reduce dose during the study “As Low As Reasonably Achievable” and uses low volume of contrast medium reducing chances of its adverse effect. The studies have shown good image quality, reduced CTDI and diagnostic accuracy with it.