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Topic · Biophysics

Cell Image Analysis Techniques

Cell Image Analysis Techniques is a research topic within Biophysics. Science Explorer counts 29k research works in it since 1950. 10.0% of them reached the world's top 10% most cited for their field and year.

This cluster of papers covers advanced techniques and tools in bioimage analysis, microscopy, and high-content screening. It includes topics such as machine learning for cellular image analysis, automated neuronal morphology reconstruction, deep learning applications, and phenotypic profiling of cellular responses. The papers also discuss the use of advanced image processing methods and the integration of high-throughput microscopy in drug discovery.

  • Bioimage Analysis
  • High-Content Screening
  • Microscopy
  • Machine Learning
  • Cellular Imaging
  • Neuronal Morphology
  • Automated Analysis
  • Deep Learning
  • Image Processing
  • Phenotypic Profiling
Research works
29k
fractional, since 1950
In the world top 10%
2.9k
per year above
Top-10% rate
10.0%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+43%
the tick is no change
Largest producer
United States
36% of the 10 largest, 2022-now
Cell Image Analysis Techniques

Which countries lead Cell Image Analysis Techniques research?

By volume, the United States and China publish the most (2.5k and 1.7k works in 2022-now).

By volume, 2022-now

  1. 1 United States 2.5k works
  2. 2 China 1.7k works
  3. 3 Germany 618 works
  4. 4 India 617 works
  5. 5 United Kingdom 478 works
  6. 6 France 306 works
  7. 7 Japan 293 works
  8. 8 Italy 254 works
  9. 9 Canada 207 works
  10. 10 South Korea 188 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.

United States: 35.6%China: 23.1%Germany: 8.6%India: 8.6%6 others listed: 24.1%36%largest
United States2,544 · 35.6%China1,651 · 23.1%Germany618 · 8.6%India617 · 8.6%6 others listed1,726 · 24.1%

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

Which institutions lead Cell Image Analysis Techniques research?

By volume in 2022-now, Harvard University publishes the most Cell Image Analysis Techniques research, followed by Centre National de la Recherche Scientifique and Chinese Academy of Sciences.

By volume, 2022-now

  1. 1 Harvard UniversityUnited States 110 works
  2. 2 Centre National de la Recherche ScientifiqueFrance 101 works
  3. 3 Chinese Academy of SciencesChina 93 works
  4. 4 Helmholtz Association of German Research CentresGermany 64 works
  5. 5 Stanford UniversityUnited States 52 works
  6. 6 University of North Carolina at Chapel HillUnited States 48 works
  7. 7 National Institutes of HealthUnited States 46 works
  8. 8 Russian Academy of SciencesRussia 41 works
  9. 9 Johns Hopkins UniversityUnited States 41 works
  10. 10 Peking UniversityChina 39 works

Who are the leading researchers in Cell Image Analysis Techniques?

The most-cited researchers publishing on Cell Image Analysis Techniques include Eric S. Lander, Yoshua Bengio and Rob Knight.

  1. 1 Eric S. Lander United States 524k citations
  2. 2 Yoshua Bengio Canada 476k citations
  3. 3 Rob Knight United States 468k citations
  4. 4 Geoffrey E. Hinton Canada 454k citations
  5. 5 Richard M. Durbin United Kingdom 410k citations
  6. 6 Mark J. Daly United States 403k citations
  7. 7 Robert John Tibshirani United States 396k citations
  8. 8 Guido Kroemer France 386k citations
  9. 9 Gad A. Getz United States 364k citations
  10. 10 Hermann Brenner Germany 343k 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 Cell Image Analysis Techniques?

The most cited paper in Cell Image Analysis Techniques is "U-Net: Convolutional Networks for Biomedical Image Segmentation" (Olaf Ronneberger, Philipp F. Fischer, Thomas Brox, 2015), with 92,751 citations. Next come "Fiji: an open-source platform for biological-image analysis" (73,171) and "NIH Image to ImageJ: 25 years of image analysis" (67,169).

Most cited papers
#PaperReleasedCitations
1 U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger, Philipp F. Fischer, Thomas Brox · Lecture notes in computer science Conference paperOpen access 2015 92,751
2 Fiji: an open-source platform for biological-image analysis Johannes Schindelin, Ignacio Arganda‐Carreras, Erwin Frise et al. · Nature Methods Open access 28 Jun 2012 73,171
3 NIH Image to ImageJ: 25 years of image analysis Caroline A Schneider, Wayne S. Rasband, Kevin W. Eliceiri · Nature Methods Open access 28 Jun 2012 67,169
4 phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data Paul J. McMurdie, Susan Holmes · PLoS ONE Open access 22 Apr 2013 23,323
5 Comprehensive Integration of Single-Cell Data Tim Stuart, Andrew W. Butler, Paul Hoffman et al. · Cell Open access Jun 2019 17,471
All 100 most cited papers, with filters and sorting

Where is Cell Image Analysis Techniques research done?

The largest centres of Cell Image Analysis Techniques research in 2022-now are Beijing (China), Shanghai (China), London (United Kingdom) and Paris (France). Among places with at least 20 works in it, it is an unusually large share of all research in Heidelberg.

Largest cities, 2022-now

  1. 1 BeijingChina 303 works
  2. 2 ShanghaiChina 151 works
  3. 3 LondonUnited Kingdom 140 works
  4. 4 ParisFrance 135 works
  5. 5 New YorkUnited States 116 works
  6. 6 CambridgeUnited States 106 works
  7. 7 TokyoJapan 97 works
  8. 8 GuangzhouChina 89 works
  9. 9 SeoulSouth Korea 88 works
  10. 10 BostonUnited States 80 works

Where it is the local speciality

  1. HeidelbergDE · 54.8 works5.9×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Cell Image Analysis Techniques than the world average.

See Cell Image Analysis Techniques on the map

Where is the best place to study Cell Image Analysis Techniques?

Among universities, judged by research, Harvard University, Stanford University and Massachusetts Institute of Technology 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%10%20%mean 17.57%fractional works in this field (log) →share of work in the world top 10% →Massachusetts Instit…Harvard UniversityStanford UniversityWeizmann Institute o…
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
1Harvard UniversityUnited States 90.620.3%4.3×110 +27.5%
2Stanford UniversityUnited States 79.519.3%4.3×52 +13.4%
3Massachusetts Institute of TechnologyUnited States 71.620.6%5.3×30 +3.0%
4Weizmann Institute of ScienceIsrael 65.517.5%7.7×9 +202.8%
5University of CambridgeUnited Kingdom 61.916.6%2.7×26 +16.2%
6Tsinghua UniversityChina 61.419.9%2.0×36 +67.8%
7University College LondonUnited Kingdom 60.610.9%2.5×32 +21.8%
8Peking UniversityChina 60.516.3%2.4×39 +102.1%
9University of Hong KongChina 59.216.7%2.0×15 +76.4%
10University of California, San FranciscoUnited States 59.117.6%3.6×21 +6.3%

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 Cell Image Analysis Techniques, country by country

Is Cell Image Analysis Techniques research growing?

Output in 2022-2025 was 43% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Cell Image Analysis Techniques.

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 Cell Image Analysis Techniques as a percentage of every work published that year, 0.037% in 2024.

still counting0.020%0.040%0.060%Cell Image Analysis Techniques0.043% in 202519801990200020102020

Fractional works of Cell Image Analysis Techniques 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%Cell Image Analysis Techniques10.0% 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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