Pranjal Sahu

441 total citations
17 papers, 276 citations indexed

About

Pranjal Sahu is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Pranjal Sahu has authored 17 papers receiving a total of 276 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 7 papers in Radiology, Nuclear Medicine and Imaging and 6 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Pranjal Sahu's work include Medical Imaging Techniques and Applications (5 papers), Digital Radiography and Breast Imaging (4 papers) and AI in cancer detection (3 papers). Pranjal Sahu is often cited by papers focused on Medical Imaging Techniques and Applications (5 papers), Digital Radiography and Breast Imaging (4 papers) and AI in cancer detection (3 papers). Pranjal Sahu collaborates with scholars based in United States, Sweden and India. Pranjal Sahu's co-authors include Mallesham Dasari, Hong Qin, Dantong Yu, Samir R. Das, Aruna Balasubramanian, Arani Bhattacharya, Fei Hou, Himanshu Gupta, Wei Zhao and Kevin G. Yager and has published in prestigious journals such as IEEE Journal of Biomedical and Health Informatics, Lecture notes in computer science and Pervasive and Mobile Computing.

In The Last Decade

Pranjal Sahu

17 papers receiving 269 citations

Peers

Pranjal Sahu

CVPR

RNMI

PRM

AI

SP

N. Santhiyakumari India

Nitin Singhal South Korea

Jie Tian China

M. Ramya India

Antônio Carlos da Silva Barros Brazil

Huafeng Wang China

Bruce K. T. Ho United States

Yanan Wu China

Jahanzaib Latif China

Md Mahbubur Rahman Bangladesh

N. Santhiyakumari India

Pranjal Sahu

106 ×1.0

CVPR

59 ×0.6

RNMI

45 ×0.6

PRM

41 ×0.7

AI

23 ×0.5

SP

Citations per year, relative to Pranjal Sahu Pranjal Sahu (= 1×) peers N. Santhiyakumari

Countries citing papers authored by Pranjal Sahu

Since Specialization

Citations

This map shows the geographic impact of Pranjal Sahu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Pranjal Sahu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pranjal Sahu more than expected).

Fields of papers citing papers by Pranjal Sahu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pranjal Sahu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Pranjal Sahu. The network helps show where Pranjal Sahu may publish in the future.

Co-authorship network of co-authors of Pranjal Sahu

This figure shows the co-authorship network connecting the top 25 collaborators of Pranjal Sahu. A scholar is included among the top collaborators of Pranjal Sahu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Pranjal Sahu. Pranjal Sahu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

1.

Sahu, Pranjal, et al.. (2023). 3D Fourier Domain Adaptation for Improving CBCT Tooth Segmentation Under Scanner Parameter Shift. 1–5. 2 indexed citations

2.

Sahu, Pranjal, et al.. (2023). Deep-learning convolutional neural network-based scatter correction for contrast enhanced digital breast tomosynthesis in both cranio-caudal and mediolateral-oblique views. Journal of Medical Imaging. 10(S2). S22404–S22404. 7 indexed citations

3.

Sahu, Pranjal, et al.. (2022). DeepMTL Pro: Deep Learning Based Multiple Transmitter Localization and Power Estimation. Pervasive and Mobile Computing. 82. 101582–101582. 20 indexed citations

4.

Sahu, Pranjal, et al.. (2022). Wavelet Guided 3D Deep Model to Improve Dental Microfracture Detection. Lecture notes in computer science. 13540. 150–160. 2 indexed citations

5.

Sahu, Pranjal, et al.. (2022). Offence Detection in Dravidian Languages Using Code-Mixing Index-Based Focal Loss. SN Computer Science. 3(5). 3 indexed citations

6.

Sahu, Pranjal, Samuel Gerber, Qingyu Zhao, et al.. (2022). Thin shell demons for dental scan registration. 1611. 99–99. 1 indexed citations

7.

Vicory, Jared, et al.. (2022). Automated fractured femur segmentation using CNN. ScholarSphere (Penn State Libraries). 104–104. 1 indexed citations

8.

Doddapaneni, Sumanth, et al.. (2021). Bitions@DravidianLangTech-EACL2021: Ensemble of Multilingual Language Models with Pseudo Labeling for offence Detection in Dravidian Languages. 291–299. 1 indexed citations

9.

Sahu, Pranjal, et al.. (2021). DeepMTL: Deep Learning Based Multiple Transmitter Localization. 41–50. 17 indexed citations

10.

Dasari, Mallesham, et al.. (2020). Streaming 360-Degree Videos Using Super-Resolution. 1977–1986. 97 indexed citations

11.

Sahu, Pranjal, et al.. (2020). Scatter correction with deep learning approach for contrast enhanced digital breast tomosynthesis (CEDBT) in both cranio-caudal (CC) view and mediolateral oblique (MLO) view. 99–99. 3 indexed citations

12.

Sahu, Pranjal, et al.. (2020). Effect of scatter correction on image noise in contrast-enhanced digital breast tomosynthesis. 25–25. 1 indexed citations

13.

Sahu, Pranjal, et al.. (2020). Structure Correction for Robust Volume Segmentation in Presence of Tumors. IEEE Journal of Biomedical and Health Informatics. 25(4). 1151–1162. 7 indexed citations

14.

Sahu, Pranjal, et al.. (2019). Using Virtual Digital Breast Tomosynthesis for De-Noising of Low-Dose Projection Images. 1647–1651. 10 indexed citations

15.

Sahu, Pranjal, Dantong Yu, Mallesham Dasari, Fei Hou, & Hong Qin. (2018). A Lightweight Multi-Section CNN for Lung Nodule Classification and Malignancy Estimation. IEEE Journal of Biomedical and Health Informatics. 23(3). 960–968. 74 indexed citations

16.

Sahu, Pranjal, Dantong Yu, & Hong Qin. (2018). Apply lightweight deep learning on internet of things for low-cost and easy-to-access skin cancer detection. 37–37. 27 indexed citations

17.

Sahu, Pranjal, Dantong Yu, Kevin G. Yager, Mallesham Dasari, & Hong Qin. (2018). In-Operando Tracking and Prediction of Transition in Material System using LSTM. 1–4. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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