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Aycromo platform uses deep learning for rapid chromosome detection

Researchers have developed Aycromo, an open-source desktop platform designed to assist in cytogenetic analysis for diagnosing genetic diseases. This platform leverages deep learning models, specifically YOLOv11, to automate chromosome detection in metaphase images, achieving a 99.40% mAP@50. Aycromo integrates pre-trained models, a benchmarking module, and an interactive annotation interface, significantly reducing analysis time from days to seconds. AI

影响 Accelerates genetic disease diagnosis by automating chromosome detection, enabling faster clinical analysis.

排序理由 This is a research paper describing an open-source platform and its performance on a specific task.

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

Aycromo platform uses deep learning for rapid chromosome detection

报道来源 [2]

  1. arXiv cs.CV TIER_1 English(EN) · Jorge L. A. Lima, Filipe R. Cordeiro ·

    Aycromo: An Open-Source Platform for Automatic Chromosome Detection in Metaphase Images Based on Deep Learning

    arXiv:2604.24685v1 Announce Type: new Abstract: Chromosome analysis is a fundamental step in the diagnosis of genetic diseases, but the manual karyotyping workflow is time-consuming and heavily dependent on expert specialists, often requiring several days per patient. Although De…

  2. arXiv cs.CV TIER_1 English(EN) · Filipe R. Cordeiro ·

    Aycromo: An Open-Source Platform for Automatic Chromosome Detection in Metaphase Images Based on Deep Learning

    Chromosome analysis is a fundamental step in the diagnosis of genetic diseases, but the manual karyotyping workflow is time-consuming and heavily dependent on expert specialists, often requiring several days per patient. Although Deep Learning models have achieved high performanc…