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Medical image analysis

ISSN 1361-8423· EN

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41.5 / 100
Journament Score
Below Average
Ranked #3,006 of 29,324 scored journals (33,995 indexed)
12 Articles
Scores higher than 89.7% of scored journals
050100
The Journament Score is computed from platform statistics — reader engagement, accessibility, publication timeliness, keyword breadth, community impact and content distribution — into a single 0–100 figure, recalculated as new articles and metadata are indexed. Dimensions that cannot be measured for this journal are excluded rather than estimated. It is independent of the paid AI Quality Analysis, which never affects this score or the ranking. Full methodology →

About This Journal

Short Name Med Image Anal
Abbreviated Name med image anal
ISSN 1361-8423

Quality Profile

5 of 12 dimensions measured
Engagement 30.4
Timeliness 0.0
Innovation 70.0
Community Impact 15.0
Content Distribution 87.0
This journal Average of scored journals
Platform statistics — the free Journament Score AI Quality Analysis — separate paid product, ranks nothing

7 of the 12 dimensions could not be measured for this journal. They are left out entirely rather than plotted as zero, and with 5 dimensions measured there is not enough of a profile to draw as a shape.

Show the numbers
Dimension This journal Corpus average
Engagement 30.4 30.4
Accessibility — 19.1
Timeliness 0.0 9.2
Diversity — 25.8
Innovation 70.0 27.4
Community Impact 15.0 7.8
Content Distribution 87.0 88.6
Content Quality — 55.5
Ethics & Transparency — 40.2
Editorial Standards — 33.4
Publication Regularity — 53.2
Geographic Reach — 30.8

Publications Per Year

Articles (12)

2019
Multi-modal neuroimaging feature selection with consistent metric constraint for diagnosis of Alzheimer's disease.
Hao, Xiaoke;Bao, Yongjin;Guo, Yingchun;Yu, Ming;Zhang, Daoqiang;Risacher, Shannon L;Saykin, Andrew J;Yao, Xiaohui;Shen, Li;, ;
Vol. 60 , pp. 101625
420 views DOI Abstract
2020
Weakly supervised instance learning for thyroid malignancy prediction from whole slide cytopathology images.
Dov, David;Kovalsky, Shahar Z;Assaad, Serge;Cohen, Jonathan;Range, Danielle Elliott;Pendse, Avani A;Henao, Ricardo;Carin, Lawrence;
Vol. 67 , pp. 101814
405 views DOI Abstract
2020
Multi-atlas image registration of clinical data with automated quality assessment using ventricle segmentation.
Dubost, Florian;Bruijne, Marleen de;Nardin, Marco;Dalca, Adrian V;Donahue, Kathleen L;Giese, Anne-Katrin;Etherton, Mark R;Wu, Ona;Groot, Marius de;Niessen, Wiro;Vernooij, Meike;Rost, Natalia S;Schirmer, Markus D;
Vol. 63 , pp. 101698
397 views DOI Abstract
2019
Adversarial learning for mono- or multi-modal registration.
Fan, Jingfan;Cao, Xiaohuan;Wang, Qian;Yap, Pew-Thian;Shen, Dinggang;
Vol. 58 , pp. 101545
375 views DOI Abstract
2019
Evaluation of algorithms for Multi-Modality Whole Heart Segmentation: An open-access grand challenge.
Zhuang, Xiahai;Li, Lei;Payer, Christian;Štern, Darko;Urschler, Martin;Heinrich, Mattias P;Oster, Julien;Wang, Chunliang;Smedby, Örjan;Bian, Cheng;Yang, Xin;Heng, Pheng-Ann;Mortazi, Aliasghar;Bagci, Ulas;Yang, Guanyu;Sun, Chenchen;Galisot, Gaetan;Ramel, Jean-Yves;Brouard, Thierry;Tong, Qianqian;Si, Weixin;Liao, Xiangyun;Zeng, Guodong;Shi, Zenglin;Zheng, Guoyan;Wang, Chengjia;MacGillivray, Tom;Newby, David;Rhode, Kawal;Ourselin, Sebastien;Mohiaddin, Raad;Keegan, Jennifer;Firmin, David;Yang, Guang;
Vol. 58 , pp. 101537
354 views DOI Abstract
2020
Deep neural network models for computational histopathology: A survey.
Srinidhi, Chetan L;Ciga, Ozan;Martel, Anne L;
Vol. 67 , pp. 101813
353 views DOI Abstract
2019
Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology.
Tellez, David;Litjens, Geert;Bándi, Péter;Bulten, Wouter;Bokhorst, John-Melle;Ciompi, Francesco;van der Laak, Jeroen;
Vol. 58 , pp. 101544
353 views DOI Abstract
2019
Predicting PET-derived demyelination from multimodal MRI using sketcher-refiner adversarial training for multiple sclerosis.
Wei, Wen;Poirion, Emilie;Bodini, Benedetta;Durrleman, Stanley;Ayache, Nicholas;Stankoff, Bruno;Colliot, Olivier;
Vol. 58 , pp. 101546
351 views DOI Abstract
2019
TOP-GAN: Stain-free cancer cell classification using deep learning with a small training set.
Rubin, Moran;Stein, Omer;Turko, Nir A;Nygate, Yoav;Roitshtain, Darina;Karako, Lidor;Barnea, Itay;Giryes, Raja;Shaked, Natan T;
Vol. 57 , pp. 176-185
321 views DOI Abstract
2020
Learning a cortical parcellation of the brain robust to the MRI segmentation with convolutional neural networks.
Thyreau, Benjamin;Taki, Yasuyuki;
Vol. 61 , pp. 101639
308 views DOI Abstract
2020
Segmentation of cellular patterns in confocal images of melanocytic lesions in vivo via a multiscale encoder-decoder network (MED-Net).
Kose, Kivanc;Bozkurt, Alican;Alessi-Fox, Christi;Gill, Melissa;Longo, Caterina;Pellacani, Giovanni;Dy, Jennifer G;Brooks, Dana H;Rajadhyaksha, Milind;
Vol. 67 , pp. 101841
201 views DOI Abstract
2020
Predicting the progression of mild cognitive impairment using machine learning: A systematic, quantitative and critical review.
Ansart, Manon;Epelbaum, Stéphane;Bassignana, Giulia;Bône, Alexandre;Bottani, Simona;Cattai, Tiziana;Couronné, Raphaël;Faouzi, Johann;Koval, Igor;Louis, Maxime;Thibeau-Sutre, Elina;Wen, Junhao;Wild, Adam;Burgos, Ninon;Dormont, Didier;Colliot, Olivier;Durrleman, Stanley;
Vol. 67 , pp. 101848
249 views DOI Abstract
2020
Deep neural network models for computational histopathology: A survey.
Srinidhi, Chetan L;Ciga, Ozan;Martel, Anne L;
Vol. 67 , pp. 101813
353 views DOI Abstract
2020
Weakly supervised instance learning for thyroid malignancy prediction from whole slide cytopathology images.
Dov, David;Kovalsky, Shahar Z;Assaad, Serge;Cohen, Jonathan;Range, Danielle Elliott;Pendse, Avani A;Henao, Ricardo;Carin, Lawrence;
Vol. 67 , pp. 101814
405 views DOI Abstract
2020
Multi-atlas image registration of clinical data with automated quality assessment using ventricle segmentation.
Dubost, Florian;Bruijne, Marleen de;Nardin, Marco;Dalca, Adrian V;Donahue, Kathleen L;Giese, Anne-Katrin;Etherton, Mark R;Wu, Ona;Groot, Marius de;Niessen, Wiro;Vernooij, Meike;Rost, Natalia S;Schirmer, Markus D;
Vol. 63 , pp. 101698
397 views DOI Abstract
2020
Learning a cortical parcellation of the brain robust to the MRI segmentation with convolutional neural networks.
Thyreau, Benjamin;Taki, Yasuyuki;
Vol. 61 , pp. 101639
308 views DOI Abstract
2019
Multi-modal neuroimaging feature selection with consistent metric constraint for diagnosis of Alzheimer's disease.
Hao, Xiaoke;Bao, Yongjin;Guo, Yingchun;Yu, Ming;Zhang, Daoqiang;Risacher, Shannon L;Saykin, Andrew J;Yao, Xiaohui;Shen, Li;, ;
Vol. 60 , pp. 101625
420 views DOI Abstract
2019
Adversarial learning for mono- or multi-modal registration.
Fan, Jingfan;Cao, Xiaohuan;Wang, Qian;Yap, Pew-Thian;Shen, Dinggang;
Vol. 58 , pp. 101545
375 views DOI Abstract
2019
Predicting PET-derived demyelination from multimodal MRI using sketcher-refiner adversarial training for multiple sclerosis.
Wei, Wen;Poirion, Emilie;Bodini, Benedetta;Durrleman, Stanley;Ayache, Nicholas;Stankoff, Bruno;Colliot, Olivier;
Vol. 58 , pp. 101546
351 views DOI Abstract
2019
TOP-GAN: Stain-free cancer cell classification using deep learning with a small training set.
Rubin, Moran;Stein, Omer;Turko, Nir A;Nygate, Yoav;Roitshtain, Darina;Karako, Lidor;Barnea, Itay;Giryes, Raja;Shaked, Natan T;
Vol. 57 , pp. 176-185
321 views DOI Abstract
Journament Score
41.5/100 · Below Average
Ranked #3,006 of 29,324 scored
(33,995 journals indexed)
Platform Statistics
AI Quality Analysis
Separate paid analysis — does not affect ranking.
Journament

Overall Quality Score

41.5/100

Tier: Below Average

The Journament Overall Quality Score is a comprehensive metric that evaluates academic journals across multiple dimensions including engagement, accessibility, diversity, innovation, and community impact.

This score helps researchers, institutions, and publishers understand the holistic quality and impact of a journal beyond traditional metrics.

Engagement Score

30.4/100

Measures user interactions, views, citations, and community involvement with this journal's content.

Higher engagement scores indicate that the journal's content is actively being read, cited, and discussed within the academic community.

Accessibility Score

Not yet measured

Evaluates how easily researchers can access journal content, including open access availability, ISSN registration, and indexing.

This metric considers factors such as paywalls, open access policies, and availability across different academic databases and search engines.

Diversity Score

Not yet measured

Assesses geographic and institutional diversity of authors, editorial board composition, and topic breadth.

A diverse journal publishes work from various geographic regions, institutions, and covers a broad range of topics within its field.

Innovation Score

70.0/100

Evaluates research novelty, interdisciplinary work, and emerging topics based on AI analysis of article abstracts.

This score reflects how much the journal publishes cutting-edge research, explores new methodologies, and bridges different academic disciplines.

Community Impact Score

15.0/100

Measures scholarly contribution and real-world applications of published research.

This metric evaluates how the journal's research translates into practical applications, policy changes, and benefits to society beyond academia.

Timeliness Score

0.0/100

Evaluates recent publication activity, publication frequency, and currency of research topics.

Higher scores indicate consistent publishing schedules and timely coverage of current research trends.

Content Distribution

87.0/100

Measures how evenly reader attention spreads across the journal's articles, using the Gini coefficient of article clicks.

Higher scores mean readership is distributed across many articles rather than concentrated on one or two.

Ethics & Transparency Score

Not yet measured

Research Integrity (10% weight)

Assesses COPE standards compliance, ethical considerations in research, transparency in methodologies, and reproducibility practices.

This metric ensures the journal maintains high ethical standards and promotes transparent, trustworthy research.

Content Quality Score

Not yet measured

Academic Rigor (20% weight) + Methodology Quality (12%)

Evaluates research methodology soundness, statistical rigor, theoretical framework strength, appropriateness of research methods, data quality, and clarity & readability.

This comprehensive metric ensures published research meets the highest academic standards.

Editorial Diversity Score

Not yet measured

Author Diversity + Interdisciplinary Value (8%)

Measures geographic diversity of authors, institutional variety, editorial board composition, and cross-disciplinary connections.

Diverse editorial teams bring varied perspectives and reduce bias in academic publishing.

Publication Regularity Score

Not yet measured

Assesses consistency of publication schedule, frequency stability, and predictable output patterns.

Regular publication schedules indicate reliable journal operations and consistent workflow management.

Geographic Reach Score

Not yet measured

Evaluates international author representation, global readership distribution, and cross-border research collaboration.

Wide geographic reach indicates global impact and international recognition of the journal's research.