In the field of medical research and diagnosis, the use of medical imaging technologies has become increasingly essential in recent years. However, the storage and management of medical image datasets have become a challenge for healthcare providers and researchers. With the increasing use of medical imaging technologies, the need for efficient image storing online has grown significantly.
In this blog post, we will explore the typical size of medical image datasets and the challenges associated with storing these images online.
What Are Medical Image Datasets?
Medical image datasets are collections of images that are used for various purposes in healthcare, such as diagnosis, treatment, research, and education.
Medical image datasets can contain different types of images, such as X-rays, CT scans, MRI scans, ultrasound images, and more.
The size of a medical image dataset depends on several factors, such as:
- The number of images in the dataset
- The resolution and quality of the images
- The format and compression of the images
- The metadata and annotations associated with the images
Size of Medical Image Datasets
There is no definitive answer to what the typical size of a medical image dataset is, as different datasets may have different characteristics and requirements.
However, some examples of medical image datasets and their sizes are:
- The ChestX-ray14 dataset contains 112,120 chest X-ray images from 30,805 patients. The images are in PNG format and have a resolution of 1024 x 1024 pixels. The total size of the dataset is about 42 GB [Source].
- The LUNA16 dataset contains 888 CT scans of the lungs from the LIDC-IDRI database. The scans are in MHD format and have a resolution of 512 x 512 x varying number of slices. The total size of the dataset is about 90 GB [Source].
- The BraTS 2020 dataset contains 369 MRI scans of brain tumors from different sources. The scans are in NIfTI format and have a resolution of 240 x 240 x 155 voxels. The total size of the dataset is about 50 GB [Source].
- The ISIC Skin Lesion Analysis Towards Melanoma Detection dataset contains 23,906 dermoscopic images of skin lesions from various sources. The images are in JPEG format and have a resolution of varying x varying pixels. The total size of the dataset is about 113 GB [Source].
These examples show that medical imaging datasets can range from tens to hundreds of gigabytes in size, depending on the type and number of images, as well as the format and resolution.
However, this does not mean that bigger datasets are always better or more useful. The quality, diversity, and relevance of the images are also important factors to consider when working with medical image datasets.
Consider the specific needs and goals of each project when choosing or creating a medical image dataset.
Q. How many GB Is a CT scan?
A. A single CT scan image can range anywhere from a few hundred kilobytes to several megabytes. A full CT scan dataset can range from 20-30 GB to over 100 GB, depending on the size of each image and the number of images in the scan.
Q. How many GB Is an MRI file?
A. MRI files are typically in the range of 100 to 600 kilobytes (KB) in size, which is similar to the size of CT and ultrasound files. The actual size of an MRI file can vary widely depending on factors such as the number of images in the scan, the resolution of the images, and the compression used to store the images.