nahidhasan/radgenome-ct-reshaped-tiny

RadGenome ChestCT Reshaped Tiny Dataset

This dataset contains resized chest CT scans from the RadGenome-ChestCT dataset.

Dataset Details

• —Original Resolution: 900x900xN
• —Resized Resolution: 300x300xN
• —Format: NIfTI (.nii.gz)
• —Number of Volumes: 253
• —Space Reduction: ~89% (resized to 1/9th of original spatial dimensions)

Dataset Structure

Each entry contains:

• —volumename: Name of the CT volume file (string)
• —anatomy: Anatomical region information (string)
• —sentence: Associated radiology report sentence (string)
• —volume_path: Relative path to the .nii.gz file (string)

Columns

Usage

from datasets import load_dataset
import nibabel as nib

# Load the dataset
ds = load_dataset("nahidhasan/radgenome-ct-reshaped-tiny")

# Access dataset information
print(f"Number of samples: {len(ds['train'])}")

# Access a single entry
sample = ds['train'][0]
print(f"Volumename: {sample['volumename']}")
print(f"Anatomy: {sample['anatomy']}")
print(f"Sentence: {sample['sentence']}")
print(f"Volume path: {sample['volume_path']}")

# Download and load the NIfTI file
# nii = nib.load(sample['volume_path'])
# data = nii.get_fdata()
# print(f"Volume shape: {data.shape}")

Source

This is a resized subset of the RadGenome-ChestCT dataset.

Processing

CT volumes were resized from 900x900xN to 300x300xN using trilinear interpolation while preserving the slice dimension.