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Pulmonary Tuberculosis Edge Diagnosis System Based on MindSpore Framework: Low-cost and High-precision Implementation with Ascend 310 Chip

arXiv 2502.14885 ↗First posted 15 Feb 2025eess.IV cs.CVcited by 0

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Abstract (arXiv)

Pulmonary Tuberculosis (PTB) remains a major challenge for global health, especially in areas with poor medical resources, where access to specialized medical knowledge and diagnostic tools is limited. This paper presents an auxiliary diagnosis system for pulmonary tuberculosis based on Huawei MindSpore framework and Ascend310 edge computing chip. Using MobileNetV3 architecture and Softmax cross entropy loss function with momentum optimizer. The system operates with FP16 hybrid accuracy on the Orange pie AIPro (Atlas 200 DK) edge device and performs well. In the test set containing 4148 chest images, the model accuracy reached 99.1% (AUC = 0.99), and the equipment cost was controlled within 150, providing affordable AI-assisted diagnosis scheme for primary care.

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References · 12

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  7. 2020Reliable Tuberculosis Detection using Chest X-ray with Deep Learning, Segmentation and Visualizationcited by 50
  8. 2024Explainable Artificial Intelligence for Medical Applications: A Reviewcited by 12
  9. 2024MedAide: Leveraging Large Language Models for On-Premise Medical Assistance on Edge Devicescited by 9
  10. 2024S-E Pipeline: A Vision Transformer (ViT) based Resilient Classification Pipeline for Medical Imaging Against Adversarial Attackscited by 1
  11. 2024Democratizing MLLMs in Healthcare: TinyLLaVA-Med for Efficient Healthcare Diagnostics in Resource-Constrained Settingscited by 1
  12. 2025Can Domain Experts Rely on AI Appropriately? A Case Study on AI-Assisted Prostate Cancer MRI Diagnosiscited by 1

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