tda4biomedicalimaging: MICCAI 2022- TDA for Biomedical Imaging Workshop medical imaging Singapore, Singapore, September 22, 2022 |
Conference website | https://sites.google.com/view/tda4biomedicalimaging/home?authuser=0 |
Submission link | https://easychair.org/conferences/?conf=tda4biomedicalimagin |
Abstract registration deadline | June 27, 2022 |
Submission deadline | June 27, 2022 |
Background
Recent years have witnessed an increasing interest in the role topology plays in machine learning and data science. Topology offers a collection of techniques and tools that have matured to a field known today as Topological Data Analysis (TDA). TDA provides a general and multi-purpose set of robust tools that have shown excellent performance in several real-world applications. These tools are naturally applicable to numerous types of data including images, points cloud, graphs, meshes, time-varying data and more. TDA techniques have been increasingly used with other techniques such as deep learning to increase the performance, and generalizability of a generic learning task. Further, the properties of the topological tools allow discovering complex relationships and separating signals that are hidden in the data from noise. Finally, topological methods naturally lend themselves to visualization rendering them useful for for tasks that require interpretability and explainability.
All these properties of topological-based methods strongly motivate the adoption of TDA tools to various applications and domains including neuroscience, bioscience, biomedicine, and medical imaging. This workshop will focus on using TDA techniques to enhance the performance, generalizability, efficiency, and explainability of the current methods applied to medical data. In particular, the workshop will focus on using TDA tools solely or combined with other computational techniques (e.g., feature engineering and deep learning) to analyze medical data including images/videos, sounds, physiological, texts and sequence data. The combination of TDA and other computational approaches is more effective in summarizing, analyzing, quantifying, and visualizing complex medical data. This workshop will bring together mathematicians, biomedical engineers, computer scientists, and medical doctors for the purpose of showing the strength of using TDA-based tools for medical data analysis.
Scope
We welcome submissions that present how TDA techniques, solely or combined with other computational techniques, have been, or potentially could be, employed to tackle interesting problems in several areas of medical data computing and computer-assisted intervention. Topics of interest include, but are not limited to:
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Ensemble of topological and deep learning models for medical applications
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Topological-based approaches for disease diagnosis, monitoring, and prediction
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Topological-based approaches for classification and segmentation (e.g., level sets, graph cuts and fuzzy connectedness)
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Topological-based approaches for medical signal processing (e.g., images, audio, texts, etc.)
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Topological-based approaches for personalized medicine
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Shape models and analysis for medical data
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Topological-based learning and optimizations for medical applications
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Topological-based medical data registration, summarization, and enhancement
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Explainability, interpretability, and visualization of medical data
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Scalable TDA methods for medical records
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Topological Structures for the Analysis of biomedical data
Important Dates
27 June (AOE) Paper submissions due.
18 July 2021 Notification of paper decisions
30 July 2021 Camera ready papers due
22 September Workshop date
Date
22 September
Submission Instructions
We welcome full length papers submission.
Full Length Papers: We encourage the submissions full length papers (8 pages excluding references) describing new work that has not been previously published, accepted for publication, or submitted for review at another venue during our review period. Accepted papers will be presented as orals and published with MICCAI Proceedings in the Springer LNCS Series.
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The reviewing process is double-blind. The papers will be evaluated by external reviewers and Area Chairs.
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Authors of all accepted papers will be invited to present their work either as a poster or an oral. .
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We strongly encourage authors to highlight the contribution of all authors in the paper.
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We strongly encourage authors to improve the reproducibility of their research along three directions: open data, open implementations, and appropriate evaluation design and reporting.
Paper template: Please use the most recent Miccai template.
Attendance Awards
Attendance grants will be awarded to a selected number of accepted papers. Unfortunately, we are unable to guarantee award grants to all accepted papers. Final grant amounts will depend on the number of applications received and will be announced after acceptance notifications. The grants will be used to cover the cost of attending the workshop and registering in the event. Grant recipients will be asked to provide receipts for expenses prior to receiving their award. The reimbursements will be sent shortly after the workshop.
Registration Instructions
This is a MICCAI2022 workshop, so your registration should be handled via MICCAI2022 webpage. Make sure your MICCAI2022 registration includes workshops.
Submission Guidelines
Authors should avoid providing information that may identify them in the acknowledgments (e.g., co-workers and grant IDs) or citations. Avoid providing links to websites that may identify any of the authors. Violation of any of these guidelines may lead to rejection without further review. All papers will be reviewed by at least three referees.