D Santhosh Reddy: PhD Student



D Santhosh Reddy

D Santhosh Reddy

PhD Research Scholar

Joined: Jul. 2015


Wireless Networks (WiNeT) Lab

Department of Electrical Engineering,

Indian Institute of Technology Hyderabad

Kandi,Sangareddy,Telangana -502285

Email :ee15resch11005@iith.ac.in


Research Interests:

Computer vision, Deep learning, Machine learning, VLSI physical design, Medical image processing, AI for healthcare

Technical Skills:

Languages: C, Python, Matlab, Verilog HDL, VHDL

Frameworks: Tensor Flow, Keras, PyTorch

EDA Tools: Synopsys-IC Compiler, DC Compiler, Cadence-Encounter, Calibre, Matlab, Xilinx ISE 14.4.

Research Work: IoT Enabled Ultrasound Medical Image Analysis using Deep Learning Techniques

Abstract:

In rural communities, there are several unpreventable healthcare complications that leads to significant morbidity and mortality when left untreated. The lack of access to the medical imaging diagnosis is one of the main factor that contribute to the greater mortality rates in rural communities. To address this issue, we are developing IoT enabled artificial intelligence based guided and automated diagnostic system for ultrasound imaging systems to ensure that person with minimum expertise can provide non-invasive imaging diagnostic in remote healthcare. The semi-skilled persons are assisted with deep learning algorithms to scan the patients in remote healthcare in case of no data-connectivity.

Santhosh Poster

Journal Publications

  1. Rajalakshmi, P., D. Santhosh Reddy, and R. Bharath. "CNN based framework for representative detection of liver images for CAD and tele-sonography applications." CSI Transactions on ICT, CSIT (2019) 7: 131. DOI: 10.1007/s40012-019-00244-9
  2. A. Z. Mohammed, A. K. Nain, J. Bandaru, A. Kumar, D. S. Reddy and R. Pachamuthu, "A Residual Phase Noise Compensation Method for IEEE 802.15.4 Compliant Dual-Mode Receiver for Diverse Low Power IoT Applications," in IEEE Internet of Things Journal, vol. 6, no. 2, pp. 3437-3447, April 2019. DOI: 10.1109/JIOT.2018.2884654

Conference Papers

  1. D. S. Reddy and P. Rajalakshmi, "A Novel Web Application Framework for Ubiquitous Classification of Fatty Liver Using Ultrasound Images," 2019 IEEE 5th World Forum on Internet of Things (WF-IoT), Limerick, Ireland, 2019, pp. 502-506. DOI: 10.1109/WF-IoT.2019.8767283
  2. R. Bharath, P. Kumar, D. S. Reddy and P. Rajalakshmi, "Compact and Programmable Ultrasound Front-End Processing Module for Research Activities, " 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Honolulu, HI, 2018, pp. 921-924. DOI: 10.1109/EMBC.2018.8512343
  3. D. S. Reddy, R. Bharath and P. Rajalakshmi, "A Novel Computer-Aided Diagnosis Framework Using Deep Learning for Classification of Fatty Liver Disease in Ultrasound Imaging," 2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom), Ostrava, 2018, pp. 1-5. DOI: 10.1109/HealthCom.2018.8531118 (Received “Outstanding Paper Award”)
  4. D. S. Reddy, R. Bharath and P. Rajalakshmi, "Classification of Nonalcoholic Fatty Liver Texture Using Convolution Neural Networks," 2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom), Ostrava, 2018, pp. 1-5. DOI: 10.1109/HealthCom.2018.8531193
  5. P. K. Mishra, B. Jagadish, M. P. R. S. Kiran, P. Rajalakshmi and D. S. Reddy, "A Novel Classification for EEG Based Four Class Motor Imagery Using Kullback-Leibler Regularized Riemannian Manifold," 2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom), Ostrava, 2018, pp. 1-5. DOI: 10.1109/HealthCom.2018.8531086
  6. R. Bharath, D. S. Reddy, P. Kumar and P. Rajalakshmi, "Novel architecture for wireless transducer based ultrasound imaging system," 2016 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES), Kuala Lumpur, 2016, pp. 432-436. DOI: 10.1109/IECBES.2016.7843487 (Received “Outstanding Paper Award”)