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Myomatlas

Myomatlas is an open, image-based decision-support tool for abnormal uterine bleeding, one of the most common and most under-addressed problems in women's health.

Core trick

A U-Net segments fibroids and measures their position relative to the cavity and serosa, then Claude classifies them against an encoded FIGO guideline.

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Description

Myomatlas is an open, image-based decision-support tool for abnormal uterine bleeding, one of the most common and most under-addressed problems in women's health. Heavy menstrual bleeding affects up to one in three women and is a leading cause of anemia, yet when fibroids are the cause, their exact location, which determines the right treatment and whether the uterus can be preserved, is often reported inconsistently and rarely explained to the patient. I built an end-to-end pipeline on the open UMD MRI dataset. A U-Net I trained segments the uterine wall, cavity and each fibroid from a pelvic MRI and measures each lesion's size and its position relative to the cavity and serosa. A Claude agent then reasons strictly from an encoded FIGO and PALM-COEIN guideline to classify each fibroid, show its justification, flag when malignancy exclusion is warranted, and derive management options, including uterus- and fertility-preserving ones. The result is presented as an interactive 3D view, a structured clinical report, and a plain-language patient explanation, with a PDF export. The key finding is that the same scan should not always lead to the same recommendation. When I add patient context, a 34-year-old who wants children versus a 58-year-old with postmenopausal bleeding, the agent's malignancy assessment and its ordering of treatment options change accordingly, from uterus-preserving management to flagging for malignancy exclusion. This matters because it makes the location-to-treatment-to-fertility logic explicit and understandable, for both clinicians and patients, in an area of medicine where women are too often unheard.
Cybarose/myomatlas★ 10 forksPythonMITCreated Jul 11, 2026 · last push Jul 14, 2026

README excerpt

# Myomatlas

Open, image-based decision support for abnormal uterine bleeding.

Myomatlas turns a pelvic MRI into a structured, guideline-based reading of uterine
fibroids. Computer vision segments each fibroid, a Claude agent classifies it by the
FIGO and PALM-COEIN systems from an encoded guideline, and the tool produces a
structured clinical report, a plain-language patient explanation, and an interactive
3D view. The analysis adapts to patient context such as age, menopausal status and
fertility desire.

This is decision support, not a diagnosis. A clinician makes the final decision.

Built for the Built with Claude: Life Sciences hackathon (Anthropic and Cerebral Valley,
in partnership with Gladstone Institutes).

## Demo

Watch the demo video: https://youtu.be/LOoYQ1xTpTA?si=1nQa9fMtH0KfOnne

<img width="1271" height="794" alt="Bildschirmfoto 2026-07-13 um 15 53 56" src="https://github.com/user-attachments/assets/031ee87a-bf6c-4971-8264-75167f89cd93" />


## The problem

Heavy or abnormal uterine bleeding affects a large share of women, is a leading cause
of iron-deficiency anemia, and is often normalized or under-investigated. When fibroids
are the cause, their location (the FIGO type) drives the right treatment, but this is
reported inconsistently and rarely explained to the patient in an understandable way.
The location also determines fertility impact and whether a uterus-preserving option
is possible. Myomatlas makes this location-to-options-to-fertility logic expl

Team