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Digital Imaging for Blood Diseases
TopicLeading institutions, researchers & key papers
This cluster of papers focuses on the automated analysis of blood cell images, particularly in the context of detecting malaria parasites and classifying leukemia. The research utilizes techniques such as image processing, convolutional neural networks, and machine learning for tasks including white blood cell segmentation, feature extraction, and automated diagnosis from microscopic blood images.
151
Works
IDs:OpenAlex
How has Digital Imaging for Blood Diseases's publication output changed over time?
ScholarIQpublication output · 2016–2024
Output grew0% over the shown period — from 1 works in 2016 to 1 in 2024.
1
1
2
2
1
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3
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1
201620172018201920202021202220232024
What are the most-cited papers on Digital Imaging for Blood Diseases?
ScholarIQmost cited works
Accurate leukocyte detection based on deformable-DETR and multi-level feature fusion for aiding diagnosis of blood diseases
Yifei Chen, Chenyan Zhang, Ben Chen, Yiyu Huang, Yifei Sun, Changmiao Wang, Xianjun Fu, Yuxing Dai, Feiwei Qin, Yong Peng, Yu Gao
S44278595. 2024386 Citations
Deep Learning Based Automatic Malaria Parasite Detection from Blood Smear and Its Smartphone Based Application
K. M. Faizullah Fuhad, Jannat Ferdousey Tuba, Md. Rabiul Ali Sarker, Sifat Momen, Nabeel Mohammed, Tanzilur Rahman
Diagnostics. 2020184 CitationsOPEN ACCESS
An efficient deep Convolutional Neural Network based detection and classification of Acute Lymphoblastic Leukemia
Pradeep Kumar Das, Sukadev Meher
Expert Systems with Applications. 2021184 Citations
Fine-grained leukocyte classification with deep residual learning for microscopic images
Feiwei Qin, Nannan Gao, Yong Peng, Zizhao Wu, Shuying Shen, Artur Grudtsin
Computer Methods and Programs in Biomedicine. 2018167 Citations
Differential box counting methods for estimating fractal dimension of gray-scale images: A survey
Chinmaya Panigrahy, Ayan Seal, Nihar Kumar Mahato, Debotosh Bhattacharjee
S70718007. 2019143 Citations
Where is Digital Imaging for Blood Diseases research published, and who funds it?
ScholarIQvenues & funding sources
TOP JOURNALS
TOP FUNDERS
National Science Foundation—
NIH—
Wellcome Trust—
European Research Council—
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How much of the research on Digital Imaging for Blood Diseases is open access?
ScholarIQopen access share
33%OPEN ACCESS
Gold
33%
Green
0%
Hybrid
0%
Bronze
0%
Closed
67%
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