Dr. Sandeep Panwar Jogi, Memorial Sloan Kettering Cancer Center, United States
Based on Dr. Sandeep Panwar Jogi’s impressive profile, he appears to be a strong candidate for the Research for Best Researcher Award.
Publication profile
Education and Experience
Dr. Jogi holds a Ph.D. in Biomedical Engineering with a focus on MRI-based assessments of knee joints. His educational background includes a B.Tech and M.Tech in Biomedical Engineering, demonstrating a solid foundation in the field. With over 10 years of experience, his career spans roles as a Research Scholar at Memorial Sloan Kettering Cancer Center, Assistant Professor at various institutions, and a Biomedical Engineer. This extensive background underscores his depth of knowledge and expertise in his field.
Research and Innovations
Dr. Jogi’s research includes developing novel MR imaging devices and AI-based algorithms. His patents and publications highlight significant contributions, such as an MR-safe loading device for knee joint assessment and AI-driven solutions for MR scanning efficiency and clinical information extraction. His work on MRI-compatible devices and AI in medical imaging demonstrates his commitment to advancing healthcare technology.
Publications
- Review on brain tumor detection using digital image processing – 12 citations, 2014 📊
- Model for in-vivo estimation of stiffness of tibiofemoral joint using MR imaging and FEM analysis – 10 citations, 2021 📈
- Device for Assessing Knee Joint Dynamics During Magnetic Resonance Imaging – 5 citations, 2021 🦵
- A semi‐automatic framework based upon quantitative analysis of MR‐images for classification of femur cartilage into asymptomatic, early OA, and advanced‐OA groups – 3 citations, 2022 🦴
- Modified radial-search algorithm for segmentation of tibiofemoral cartilage in MR images of patients with subchondral lesion – 3 citations, 2020 🩺
- Explainability of Artificial Intelligence for Diagnosing COVID-19 from Chest X-Rays – 1 citation, 2021 🤖
- Automated Segmentation of Knee Cartilage Using Modified Radial Approach for OA Patients with and without Bone Abnormality – 1 citation, 2019 📉
- Automated seed points selection based radial-search segmentation method for sagittal and coronal view knee MRI imaging – 1 citation, 2017 🩻
- Novel Spin-lock Time Sampling Strategies for Improved Reproducibility in Quantitative T1ρ Mapping – No citations yet, 2024 🧪
- 4D Lung MRI with Isotropic Resolution on a 1.5T MR-Linac using a Self-Navigated 3D Radial Kooshball Acquisition and Sparse Motion Reconstruction – No citations yet, 2024 🌬️
- Accelerated Abdominal 3D T1rho Mapping using Diamond Radial Sampling – No citations yet, 2024 📉
- Quantitative 3D T1rho and T2 Mapping for Radiotherapy Treatment Response Monitoring in Head and Neck Cancer – No citations yet, 2024 🧠
- Novel Sampling Schemes of Spin-locking Times to Improve Reproducibility of Quantitative 3D T1rho Mapping – No citations yet, 2024 🔍
- Automatic Liver and Subcutaneous Fat Segmentation from MRI-PDFF Images – No citations yet, 2020 🏥
- An approach to validate MRI Compatible axial Knee joint Loading Device with various standing posture in Standing MRI – No citations yet, 2019 🦵
- Retrospective comparative study to assess the pitfalls of CartiGram and the complementary role of FSPD in the evaluation of cartilage lesions of the knee joint – No citations yet, 2019 🔬
- Evaluating variability of T2 values of the cartilage, menisci and muscles around knee joint on CartiGram sequence at 1.5 T and 3.0 T MR – No citations yet, 2019 📉
- Semi-Automatic Quantitative Analysis of Cartilage Thickness & T2 Values – No citations yet, 2018 📏
- Quantitative MR Imaging of Articular Knee cartilage with Axial Loading during Image Acquisition – No citations yet, 2018 🦵
- Automated Seed Points Selection Based Radial Search Segmentation Method for Sagittal and Coronal View Knee MRI Imaging – No citations yet, 2018 🖼️
Core Competencies
Dr. Jogi’s skills in medical image analysis, machine learning, and AI are well-aligned with the award’s criteria. His expertise in MRI, CT, X-ray modalities, and product development positions him as a leader in his field. His ability to interact with clinicians and develop novel imaging solutions showcases his practical and innovative approach to solving healthcare challenges.
Conclusion
Dr. Sandeep Panwar Jogi is a compelling candidate for the Research for Best Researcher Award. His blend of advanced education, extensive research experience, innovative contributions, and active involvement in the scientific community aligns well with the award’s objectives. His work not only advances medical imaging technologies but also demonstrates a profound impact on healthcare solutions.