Ademola E. Ilesanmi

730 total citations · 1 hit paper
15 papers, 457 citations indexed

About

Ademola E. Ilesanmi is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Ademola E. Ilesanmi has authored 15 papers receiving a total of 457 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 10 papers in Radiology, Nuclear Medicine and Imaging and 7 papers in Artificial Intelligence. Recurrent topics in Ademola E. Ilesanmi's work include AI in cancer detection (7 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and Digital Imaging for Blood Diseases (4 papers). Ademola E. Ilesanmi is often cited by papers focused on AI in cancer detection (7 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and Digital Imaging for Blood Diseases (4 papers). Ademola E. Ilesanmi collaborates with scholars based in Thailand, China and United States. Ademola E. Ilesanmi's co-authors include Stanislav S. Makhanov, Guanglin Li, Peng Fang, Xiangxin Li, Oluwarotimi Williams Samuel, Chalie Charoenlarpnopparut, Drew A. Torigian, Jayaram K. Udupa, David A. Wolk and James C. Gee and has published in prestigious journals such as SHILAP Revista de lepidopterología, Applied Sciences and Computer Methods and Programs in Biomedicine.

In The Last Decade

Ademola E. Ilesanmi

13 papers receiving 442 citations

Hit Papers

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What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Methods for image denoising using convolutional neural network: a review

2021 207 citations Ademola E. Ilesanmi et al. Complex & Intelligent Systems profile →

Peers

Countries citing papers authored by Ademola E. Ilesanmi

Since Specialization

Citations

This map shows the geographic impact of Ademola E. Ilesanmi'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 Ademola E. Ilesanmi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ademola E. Ilesanmi more than expected).

Fields of papers citing papers by Ademola E. Ilesanmi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ademola E. Ilesanmi. 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 Ademola E. Ilesanmi. The network helps show where Ademola E. Ilesanmi may publish in the future.

Co-authorship network of co-authors of Ademola E. Ilesanmi

This figure shows the co-authorship network connecting the top 25 collaborators of Ademola E. Ilesanmi. A scholar is included among the top collaborators of Ademola E. Ilesanmi 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 Ademola E. Ilesanmi. Ademola E. Ilesanmi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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15 of 15 papers shown

#	Work	Indexed citations
1	Unlocking the Power of 3D Convolutional Neural Networks for COVID-19 Detection: A Comprehensive Review 2025 ·Journal of Imaging Informatics in Medicine ·Ademola E. Ilesanmi, (unknown), (unknown), (unknown), Samir Brahim Belhaouari	1
2	Beyond Macrostructure: Is There a Role for Radiomics Analysis in Neuroimaging ? 2024 ·Magnetic Resonance in Medical Sciences ·Sandhitsu R. Das, Ademola E. Ilesanmi, David A. Wolk, James C. Gee	5
3	Reviewing 3D convolutional neural network approaches for medical image segmentation 2024 ·Heliyon ·Ademola E. Ilesanmi, (unknown), (unknown)	13
4	Auto-segmentation of thoracic brachial plexuses for radiation therapy planning 2023 ·PubMed ·Ademola E. Ilesanmi, Jayaram K. Udupa, (unknown), (unknown), Dewey Odhner, (unknown), (unknown), Sharon Lewis, (unknown), (unknown), Drew A. Torigian	0
5	A systematic review of retinal fundus image segmentation and classification methods using convolutional neural networks 2023 ·SHILAP Revista de lepidopterología ·Ademola E. Ilesanmi, (unknown), (unknown)	25
6	Organ segmentation from computed tomography images using the 3D convolutional neural network: a systematic review 2022 ·International Journal of Multimedia Information Retrieval ·Ademola E. Ilesanmi, (unknown), (unknown), Drew A. Torigian, Jayaram K. Udupa	12
7	Segmentation and Classification of Retinal Fundus Images using Convolutional Neural Networks: A systematic review of methods and latest trends 2022 ·Research Square ·Ademola E. Ilesanmi, (unknown), (unknown), Drew A. Torigian, Jayaram K. Udupa	0
8	An integrated deep learning model for motor intention recognition of multi-class EEG Signals in upper limb amputees 2021 ·Computer Methods and Programs in Biomedicine ·(unknown), Ademola E. Ilesanmi, Xiangxin Li, Oluwarotimi Williams Samuel, Peng Fang, Guanglin Li	32
9	Methods for image denoising using convolutional neural network: a review breakdown → 2021 ·Complex & Intelligent Systems ·Ademola E. Ilesanmi, (unknown)	207
10	Methods for the segmentation and classification of breast ultrasound images: a review 2021 ·Journal of Ultrasound ·Ademola E. Ilesanmi, (unknown), Stanislav S. Makhanov	27
11	Neuro-evolutionary approach for optimal selection of EEG channels in motor imagery based BCI application 2021 ·Biomedical Signal Processing and Control ·(unknown), (unknown), Ademola E. Ilesanmi, Xiangxin Li, Oluwarotimi Williams Samuel, Peng Fang, Guanglin Li	27
12	A method for segmentation of tumors in breast ultrasound images using the variant enhanced deep learning 2021 ·Journal of Applied Biomedicine ·Ademola E. Ilesanmi, (unknown), Stanislav S. Makhanov	44
13	Efficient and Accurate Hemorrhages Detection in Retinal Fundus Images Using Smart Window Features 2021 ·Applied Sciences ·(unknown), Ademola E. Ilesanmi, Chalie Charoenlarpnopparut	15
14	Multiscale hybrid algorithm for pre-processing of ultrasound images 2021 ·Biomedical Signal Processing and Control ·Ademola E. Ilesanmi, (unknown), (unknown), Stanislav S. Makhanov	29
15	Multiscale superpixel method for segmentation of breast ultrasound 2020 ·Computers in Biology and Medicine ·Ademola E. Ilesanmi, (unknown), Stanislav S. Makhanov	20

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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