Files
Lumina-MSK/workspace/LEGACY/VKIST_ML/codebase-vkist-ultrasound-legacy
DatTT127 fed5f277f4 update
2026-06-24 21:47:15 +07:00
..
2026-06-24 16:04:40 +07:00
2026-06-24 21:47:15 +07:00
2026-06-24 10:33:07 +07:00
2026-06-24 10:33:07 +07:00

VKIST Ultrasound

Introduction

VKIST Ultrasound is an application designed to support the diagnosis of knee arthritis using knee ultrasound images.
The system processes ultrasound images and assists clinicians in identifying potential signs of arthritis, providing a supportive tool for medical analysis and research.


Yêu cầu hệ thống

1. YÊU CẦU VỀ MÁY TÍNH

  • Hệ điều hành: Windows 10/11 (64-bit) hoặc Ubuntu 20.04/22.04.
  • CPU: Tối thiểu 4 nhân (khuyến nghị Intel Core i5 thế hệ 10 trở lên hoặc tương đương).
  • RAM: Tối thiểu 16GB.
  • GPU: NVIDIA GPU hỗ trợ CUDA (Kiến trúc Pascal trở lên, ví dụ: GTX 10-series, RTX series).
  • VRAM: Khuyến nghị 8GB trở lên để tối ưu tốc độ phân vùng (segmentation).

2. CÀI ĐẶT PHẦN MỀM HỖ TRỢ

  • Quản lý môi trường: Anaconda3 hoặc Miniconda.
  • Đồ họa: NVIDIA Driver tương thích với CUDA 12.4.
  • CUDA Toolkit: Phiên bản 12.4.
  • Trình biên dịch C++:

Installation

1. Clone the Repository

git clone https://github.com/itvkist/vkist-ultrasound.git
cd vkist-ultrasound

2. Create Environment and Install Dependencies

conda create -n vkist-ultrasound python=3.10 -y
conda activate vkist-ultrasound
pip install -r requirements.txt

Download Model Weights

The weights of the models can be found in the following link:

https://drive.google.com/drive/folders/1lBkplP-5uv6V2wR1CJ2COaGy1SnZxxJl

After downloading the link, unzip and copy the files into the ./models folder

Run the Application

Start the application with:

python app.py

The application will be available at:

http://localhost:8000

Notes

  • Make sure your GPU drivers are compatible with the CUDA version installed.
  • If GPU support is not required, the PyTorch CPU version can also be used.

Rules Section

Naming Convention Exception for LEGACY Code

  • Legacy code (deprecated or intended for migration) may be referenced or used in the codebase only when accompanied by a conventional comment indicating its legacy status (e.g., # LEGACY: to be refactored or # LEGACY: deprecated).
  • Such legacy code should not be extended for new features; it is intended for read/reference only or as a stepping stone toward modernization.
  • When introducing new modules or files, follow the standard naming convention (e.g., snake_case for Python files, PascalCase for classes, etc.). Legacy exceptions are exempt only when explicitly marked.

Visualization Guidelines

  • Prefer text-based diagram descriptions using PlantUML or Mermaid syntax for version control and diffability.
  • If a diagram must be drawn by hand, use raster image formats such as .png or .jpg.
  • Avoid binary formats like PDF, PPT, or other proprietary formats for diagrams in the repository.