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Topic · Computer Vision and Pattern Recognition

Digital Imaging for Blood Diseases

Digital Imaging for Blood Diseases is a research topic within Computer Vision and Pattern Recognition. Science Explorer counts 16k research works in it since 1950. 10.2% of them reached the world's top 10% most cited for their field and year.

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.

  • Malaria Parasite Detection
  • Leukemia Classification
  • Image Processing
  • Convolutional Neural Networks
  • White Blood Cell Segmentation
  • Automated Diagnosis
  • Microscopic Blood Images
  • Machine Learning
  • Feature Extraction
  • Medical Image Analysis
Research works
16k
fractional, since 1950
In the world top 10%
1.7k
per year above
Top-10% rate
10.2%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+63%
the tick is no change
Largest producer
India
41% of the 10 largest, 2022-now
Digital Imaging for Blood Diseases

Which countries lead Digital Imaging for Blood Diseases research?

By volume, India and China publish the most (1.9k and 966 works in 2022-now).

By volume, 2022-now

  1. 1 India 1.9k works
  2. 2 China 966 works
  3. 3 United States 569 works
  4. 4 Indonesia 406 works
  5. 5 Türkiye 170 works
  6. 6 Brazil 155 works
  7. 7 Pakistan 146 works
  8. 8 Bangladesh 135 works
  9. 9 United Kingdom 132 works
  10. 10 Germany 119 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

India: 40.6%China: 20.5%United States: 12.1%Indonesia: 8.6%6 others listed: 18.2%41%largest
India1,915 · 40.6%China966 · 20.5%United States569 · 12.1%Indonesia406 · 8.6%6 others listed857 · 18.2%

Shares of the rows listed above, not of the whole node.

Which institutions lead Digital Imaging for Blood Diseases research?

By volume in 2022-now, Saveetha University publishes the most Digital Imaging for Blood Diseases research, followed by SRM Institute of Science and Technology and Vellore Institute of Technology University.

By volume, 2022-now

  1. 1 Saveetha UniversityIndia 99 works
  2. 2 SRM Institute of Science and TechnologyIndia 70 works
  3. 3 Vellore Institute of Technology UniversityIndia 59 works
  4. 4 Chitkara UniversityIndia 54 works
  5. 5 Manipal Academy of Higher EducationIndia 33 works
  6. 6 Amrita Vishwa VidyapeethamIndia 33 works
  7. 7 Graphic Era UniversityIndia 30 works
  8. 8 Koneru Lakshmaiah Education FoundationIndia 28 works
  9. 9 Chandigarh UniversityIndia 27 works
  10. 10 Chinese Academy of SciencesChina 24 works

Who are the leading researchers in Digital Imaging for Blood Diseases?

The most-cited researchers publishing on Digital Imaging for Blood Diseases include Simon Iain Hay, Jost Bruno Jonas and Xiangyu Zhang.

  1. 1 Simon Iain Hay United States 452k citations
  2. 2 Jost Bruno Jonas Germany 350k citations
  3. 3 Xiangyu Zhang 327k citations
  4. 4 Luigi Ferrucci United States 281k citations
  5. 5 Charles M. Perou United States 263k citations
  6. 6 Yann LeCun United States 256k citations
  7. 7 Andrew Zisserman United Kingdom 255k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

What are the most cited papers in Digital Imaging for Blood Diseases?

The most cited paper in Digital Imaging for Blood Diseases is "Artificial neural networks: a tutorial" (Abhishek Jain, Jianchang Mao, Khalid Mohiuddin, 1996), with 4,984 citations. Next come "Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning" (4,903) and "Ridge-Based Vessel Segmentation in Color Images of the Retina" (4,213).

Most cited papers
#PaperReleasedCitations
1 Artificial neural networks: a tutorial Abhishek Jain, Jianchang Mao, Khalid Mohiuddin · Computer Mar 1996 4,984
2 Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning Daniel Kermany et al. · Cell Open access Feb 2018 4,903
3 Ridge-Based Vessel Segmentation in Color Images of the Retina Joes Staal, Michael D. Abràmoff, Meindert Niemeijer et al. · IEEE Transactions on Medical Imaging Apr 2004 4,213
4 Clinical-grade computational pathology using weakly supervised deep learning on whole slide images Gabriele S. V. Campanella, Matthew G. Hanna, Luke Geneslaw et al. · Nature Medicine Open access 15 Jul 2019 2,845
5 The Immunoglobulin Superfamily—Domains for Cell Surface Recognition Abigail Williams, A. Neil Barclay · Annual Review of Immunology Apr 1988 2,259
All 100 most cited papers, with filters and sorting

Where is Digital Imaging for Blood Diseases research done?

The largest centres of Digital Imaging for Blood Diseases research in 2022-now are Chennai (India), Beijing (China), Coimbatore (India) and Dhaka (Bangladesh). Among places with at least 20 works in it, it is an unusually large share of all research in Vijayawada, Chandigarh and Chennai.

Largest cities, 2022-now

  1. 1 ChennaiIndia 294 works
  2. 2 BeijingChina 127 works
  3. 3 CoimbatoreIndia 96 works
  4. 4 DhakaBangladesh 89 works
  5. 5 ShanghaiChina 80 works
  6. 6 BengaluruIndia 78 works
  7. 7 New DelhiIndia 77 works
  8. 8 ChandigarhIndia 66 works
  9. 9 PuneIndia 66 works
  10. 10 VelloreIndia 61 works

Where it is the local speciality

  1. VijayawadaIN · 43.1 works14×
  2. ChandigarhIN · 66.2 works9.7×
  3. ChennaiIN · 293.7 works9.0×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Digital Imaging for Blood Diseases than the world average.

See Digital Imaging for Blood Diseases on the map

Where is the best place to study Digital Imaging for Blood Diseases?

Among universities, judged by research, Chitkara University, King Abdulaziz University and Saveetha University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 18.34%fractional works in this field (log) →share of work in the world top 10% →King Abdulaziz Unive…Chitkara UniversityVellore Institute of…Saveetha University
above the meannear itbelow it

One dot per university in the first ten of the table below, at the default weights. The upper left is the interesting corner: small places doing unusually strong work.

Excellenceshare of its work in the world top 10%, 2022-now and all time averaged
40%
Specialisationhow much of its work is in this field, counted up to 10× the world share
10%
Sizeits output in this field, on a log scale
30%
Growthoutput growth, counted from -20% to +20%
10%
Internationalshare of its work with a co-author abroad
10%
Each slider sets a weight; the share it gets of the score is beside it.
#UniversityScoreTop 10%SpecialisationWorksGrowth
1Chitkara UniversityIndia 64.516.5%24.0×54 +1361.1%
2King Abdulaziz UniversitySaudi Arabia 64.234.8%3.2×10 +243.8%
3Saveetha UniversityIndia 62.18.0%17.8×99 +923.2%
4Vellore Institute of Technology UniversityIndia 60.112.1%10.3×59 +168.5%
5Manipal Academy of Higher EducationIndia 59.318.0%8.0×33 +29.6%
6Princess Nourah bint Abdulrahman UniversitySaudi Arabia 58.227.5%5.7×8 -
7King Saud UniversitySaudi Arabia 53.925.9%1.7×10 +149.8%
8SRM Institute of Science and TechnologyIndia 53.15.3%11.8×70 +387.3%
9Central South UniversityChina 50.425.9%1.4×16 +42.9%
10Graphic Era UniversityIndia 49.49.4%14.9×30 +638.3%

Universities only. The score blends excellence (40%), size (30%), specialisation (10%), growth (10%), international reach (10%), 2022-now; growth compares 2018-21 with 2022-25 and counts up to +20%, since a jump from a small base is mostly noise.

Every institution in Digital Imaging for Blood Diseases, country by country

Is Digital Imaging for Blood Diseases research growing?

Output in 2022-2025 was 63% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Digital Imaging for Blood Diseases.

still counting19801990200020102020
grewheldshrank

The same series as a ribbon: one cell per year, darker for more. The line above answers how much; this answers when.

Its share of all research

Growing output can still be a shrinking share: all of science grows. This is Digital Imaging for Blood Diseases as a percentage of every work published that year, 0.030% in 2024.

still counting0.020%0.040%Digital Imaging for Blood Diseases0.029% in 202519801990200020102020

Fractional works of Digital Imaging for Blood Diseases over all fractional works that year. How the balance of science has shifted.

How much of it reaches the world top 10%

Year by year.

still counting5%10%15%Digital Imaging for Blood Diseases10.4% in 2025200020102020

Of each year's works in it, the share that reached the world's 10% most cited for their field and year. A field is the world for its own topics, so there is no other line to hold it against.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.

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