Imaging · dataset · 2026
FollicleFinder enables automated three-dimensional segmentation of human ovarian follicles
Listed in ETH Zürich Research Collection
In vitro fertilization (IVF) treatment protocols require frequent monitoring of the ovarian follicle growth process.
Description
Current treatment protocols are financially, physically, and psychologically burdensome for the patient. Mechanistic models of folliculogenesis have the potential to improve outcomes by personalizing treatments to the individual patient, but require high-fidelity data of reliable quality.
We report FollicleFinder, an open source pipeline for state-of-the-art automated, 3D segmentation and measurement of ovarian follicles in ultrasound images. FollicleFinder was developed using local shape descriptors as an auxiliary task to improve segmentation accuracy. It was validated using expert-labeled ground truth data.
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To make FollicleFinder amenable for use by clinicians, we created a graphical user interface for performing the segmentation and interactively exploring the results. Further, we are releasing our 533 sets of raw images and expert-labeled ground truth as a benchmark dataset. Together, the open source segmentation pipeline, graphical user interface, and benchmark dataset provide a suite of tools for accurate 3D follicle segmentation and measurement instrumental for more predictive personalized IVF treatment models capable of guiding critical clinical decisions, such as dosage adjustments and trigger timing.
Links
Where it is published
- ETH Zürich Research Collection record hdl.handle.net/20.500.11850/802233 ↗
landing page · from research collection ethz ch
- DOI doi.org/10.3929/ethz-c-000802233 ↗
DOI / persistent id · from research collection ethz ch
Catalogue records · 1
- OAI-PMH record research-collection.ethz.ch/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Awww.… ↗
metadata API · from research collection ethz ch
Topics
- From keywords
- Chemistry · Computer Science & AI · Earth & Environmental Science · Economics & Finance · Engineering · Humanities · Life Sciences · Materials Science · Mathematics & Statistics · Medicine & Health · Physics · Psychology & Behavioral Science · Social Science
- Inferred from text
- Image 65% · Reproductive medicine 69%
Provenance · 1 source records, 20 field assertions
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|---|---|---|---|
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| title | source · research collection ethz ch | connector:research_collection_ethz_ch@1.0.0 | /metadata/dc/title |