Body Part Classification

Kalbe Digital Lab

Overview

The Body Part Classification program serves the critical purpose of categorizing body parts from DICOM x-ray scans into five distinct classes: abdominal, adult chest, pediatric chest, spine, and others. This program trained using ResNet18 model.

Dataset

The program has been meticulously trained on a robust and diverse dataset, specifically VinDrBodyPartXR Dataset..
This dataset is introduced by Vingroup of Big Data Institute which include 16,093 x-ray images that are collected and manually annotated. It is a highly valuable resource that has been instrumental in the training of our model.

  • Objective: Body Part Identification
  • Task: Classification
  • Modality: Grayscale Images

Model Architecture

The model architecture of ResNet18 to train x-ray images for classifying body part.

model-architecture

Demo

Please select or upload a body part x-ray scan image to see the capabilities of body part classification with this model