PMRAM: Bangladeshi Brain Cancer - MRI Dataset

This Bangladeshi Brain Cancer MRI Dataset is a large dataset of Magnetic Resonance Imaging (MRI) images created to aid researchers in medical diagnosis, especially for brain cancer research. This collection contains a total of 1600 raw photos (every class have 400 raw images) after augmentation it contains total 6000 images, which are wisely divided into four main categories as:

Glioma -1500 images

Meningioma -1500 images

Pituitary-1500 images

No Tumor-1500 images

All the images in this dataset were collected from different hospitals around Bangladesh. It brought diversity and representation into the sample. To make the images compatible with various image processing, machine learning and deep-learning pipelines as possible they are then resized to a standardize size of 512×512.

This dataset is incredibly significant since high-quality data, such as medical imaging data, are few and difficult to obtain, particularly in the context of brain cancer. Assume that four prominent doctors collaborate on data collection in order to give more accurate and helpful content. It made it feasible. The cooperation emphasizes the dataset's potential to improve medical practice today by providing a dependable supply of diagnoses for use in diagnostic tool creation and testing within current medicine.

This dataset can be used by researchers and practitioners for a variety of applications such as Dense net 201, yolov8x/s, CNN, resnet50v2, VGG-16, MobilenetV2 etc.

Image Processing Details:

Images are randomly rotated within a range of 45 degrees. (rotation range=45)

Images are horizontally shifted by up to 20% of the width of the image. (width_shift_range=0.2)

Images are vertically shifted by up to 20% of the height of the image. (height_shift_range=0.2)

Shear transformation is applied to the image within a range of 20%. (shear range=0.2)

Images are randomly zoomed in or out by up to 20%. (zoom range=0.2)

Images are randomly flipped horizontally. (horizontal flip=True)

When transformations like rotations or shifts leave empty areas in the image, they are filled in by the nearest pixel values. (fill mode='nearest')

Hospital List(for Data Collection):

Ibn Sina Medical College, Kollanpur, 1, 1-B Mirpur Rd, Dhaka 1207

Dhaka Medical College & Hospital, Secretariat Rd, Dhaka 1000

Cumilla Medical College, Kuchaitoli, Dr. Akhtar Hameed Khan Road, Cumilla 3500, Bangladesh

Supervisor & investigator:

Md. Mizanur Rahman

Lecturer,

Computer Science and Engineering

Daffodil International University

Dhaka, Bangladesh

[e-mail]

Data Collectors:

Md Shahriar Mannan Prottoy

Mahtab Chowdhury

Redwan Rahman

Azim Ullah Tamim