International Symposium on Biomedical Imaging

Top Research Topics at International Symposium on Biomedical Imaging?

• Artificial intelligence (69.23%)
• Computer vision (42.15%)
• Pattern recognition (31.63%)

The conference mostly deals with topics like Artificial intelligence, Computer vision, Pattern recognition, Segmentation and Image segmentation. The study on Artificial intelligence presented is investigated in conjunction with research in Magnetic resonance imaging. The conference focused on Computer vision research but expanded to cover Algorithm.

Most of the works presented in the conference deals with Algorithm but it intersects with the subject of Mathematical optimization. While Pattern recognition is the focus of the event, it also provided insights into the studies of Contextual image classification, Voxel, Artificial neural network and Feature (computer vision). Specifically, studies on Scale-space segmentation are prevalent in the Segmentation works discussed.

Segmentation-based object categorization is a major topic of Scale-space segmentation research. It explores issues in Iterative reconstruction which can be linked to other research areas like Imaging phantom, Tomography, Optics and Compressed sensing.

What are the most cited papers published at the conference?

• Ilastik: Interactive learning and segmentation toolkit (802 citations)
• Skin lesion analysis toward melanoma detection: A challenge at the 2017 International symposium on biomedical imaging (ISBI), hosted by the international skin imaging collaboration (ISIC) (726 citations)
• A method for normalizing histology slides for quantitative analysis (505 citations)

Research areas of the most cited articles at International Symposium on Biomedical Imaging:

The conference articles primarily tackle Artificial intelligence, Computer vision, Pattern recognition, Image segmentation and Segmentation. The conference articles facilitate discussions on Computer vision that incorporate concepts from other fields like Algorithm and Magnetic resonance imaging. While work presented in the conference papers provide substantial information on Pattern recognition, it also covers topics in Cancer and Machine learning.

Papers citation over time

A key indicator for each conference is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

Top authors and change over time

The top authors publishing at International Symposium on Biomedical Imaging (based on the number of publications) are:

• Paul M. Thompson (100 papers) published 10 papers at the last edition, 3 more than at the previous edition,
• Tianming Liu (57 papers) published 9 papers at the last edition, 2 more than at the previous edition,
• Arthur W. Toga (55 papers) absent at the last edition,
• Michael Unser (54 papers) published 3 papers at the last edition, 1 more than at the previous edition,
• Daniel Rueckert (52 papers) published 2 papers at the last edition the same number as at the previous edition.

The overall trend for top authors publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top authors.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing at International Symposium on Biomedical Imaging (based on the number of publications) are:

• University of California, Los Angeles (117 papers) published 3 papers at the last edition,
• French Institute for Research in Computer Science and Automation (109 papers) published 4 papers at the last edition, 5 less than at the previous edition,
• University of Oxford (84 papers) published 3 papers at the last edition, 3 less than at the previous edition,
• University of Pennsylvania (80 papers) absent at the last edition,
• French Institute of Health and Medical Research (77 papers) published 3 papers at the last edition, 2 more than at the previous edition.

The overall trend for top affiliations publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions at the conference edition to all articles published within that conference. The best research institutions were selected based on the largest number of articles published during all editions of the conference.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2017 edition, 1.03% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 12.20% were posted by at least one author from the top 10 institutions publishing at the conference. Another 13.59% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 20.56% of all publications and 53.66% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of conferences they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same conference from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the conference in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing at a conference. The index includes the authors publishing at the last edition of a conference, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.