Publications

Poster Presentation

1. Towards AI based Freehand 3D Ultrasound Reconstruction , IEEE SAUS 2024, IIT Gandhinagar.

2. AI-Assisted Fetal Head Anatomical Plane Detection in Secure Ultrasound Reconstructed Volumetric Data, 3rd MS Divisional Research Symposium in "Applications of AI-ML in Engineering" at IISc Bangalore.

3.  Detection of Anatomical Structures of a Fetal Phantom in Ultrasound Using YOLO,  IISc-Siemens Workshop on Artificial Intelligence in Precision Medicine at IISc Bangalore.

4. AI-Assisted Fetal Head Anatomical Plane Detection for Remote Antenatal Screening. Ripples in Dept of Design and Manufacturing, IISc Bangalore.

Publications 

1. Pravallika Saladi, Pavan K.M. and M. Arora, “Automatic Detection of Anatomical Structures in Freehand Fetal Ultrasound: A Comparative Evaluation of YOLO Variants,” 2026 IEEE Engineering in Medicine and Biology Conference (EMBC), Toronto, Canada. Presented.

2. P. Saladi and M. Arora, "Anatomical Plane Classification for Fetal Head Ultrasound - Addressing Class Imbalance with Deep Learning," 2025 IEEE International Biomedical Instrumentation and Technology Conference (IBITeC), Yogyakarta, Indonesia, 2025, pp. 89-94, doi: 10.1109/IBITeC66306.2025.11473194.

3. P. Saladi and Y. Kalepu, "Electromagnetic Inverse Scattering Problem Solved by DConvNet and Adapted Attention U-Net," 2023 IEEE 12th International Conference on Communication Systems and Network Technologies (CSNT), Bhopal, India, 2023, pp. 101-104, doi: 10.1109/CSNT57126.2023.10134734. 

Abstract: A two-stage Deep Learning strategy for resolving the electromagnetic inverse scattering problem (ISP) is proposed in this paper. The two steps involve utilizing Deep Convolutional Neural Network (DConvNet) to draw out features from the Scattered field data and refine the image reconstruction using adapted version of Attention U-Net. We observed that our proposed method delivered better results in terms of image quality and reconstruction precision. Moreover, we observed the outcomes of Attention U-Net, DConvNet, and DRCNN for ISP and found that Attention U-Net gave better image refinement.

4. Pravallika Saladi, Yaswanth Kalepu. Deep Learning Strategy for Resolving Electromagnetic Inverse Scattering Problem with Phase-less Data. Authorea. July 27, 2023. DOI: 10.22541/au.169045202.28967646/v1