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Dataset . 2021
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2021
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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A Positive/Unlabeled Approach for the Segmentation of Medical Sequences using Point-Wise Supervision

Authors: Lejeune, Laurent; Sznitman, Raphael;

A Positive/Unlabeled Approach for the Segmentation of Medical Sequences using Point-Wise Supervision

Abstract

Description ------------ This archive contains data and results (model checkpoint, segmentation results, ...) used and obtained in paper: Laurent Lejeune, Raphael Sznitman, A Positive/Unlabeled Approach for the Segmentation of Medical Sequences using Point-Wise Supervision, Medical Image Analysis, 2021 (in preparation) Details ------------ Each directory is named DatasetXY, where X denotes the type (surgical instrument, cochlea, slitlamp, and brain), and Y denotes the index of the sequences (from 0 to 3). For the data.zip archive, we provide a CSV file that contains the 2d locations used in our experiments. For the results.zip archive, the checkpoint of our models are in PyTorch format.

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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