Abstract 

Microscopic image based analysis plays an important role in histopathological computer based diagnostics. Identification of childhood medulloblastoma and its proper subtype from biopsy tissue specimen of childhood tumor is an integral part for prognosis.The dataset is of Childhood medulloblastoma (CMB) biopsy samples. The images are of 10x and 100x microscopic magnifications, uploaded in separate folders. The images consist of normal brain tissue cell samples and CMB cell samples of different WHO defined subtypes. An excel sheet is also uploaded for ease of data description. The images are .jpeg images at standard RGB color format with 24 bit depth. The images are obtained by observing the medical slides under microscope where a camera was mounted to the computer that captures the microscopic images. We have collected a total of 202 and 153 images of 10x and 100x respectively. Number of pateints was 11. No direct pateint information was disclosed during the whole procedure and data was collected by the standard operating procedure of the medical centers. The images are obtained under clinical supervision of the medical centers.  

 

Instructions: 

The dataset contains two folder of diffrent magnification images, i.e; 10x and 100x. The type of each image is described in the provided excel file. Each slide has a unique number and the number in bracket denotes that the corresponding image is of the single slide. 

Comments

Dear sir, I would like to work on this dataset to develop algorithms for Image Classification based on deep learning networks.

Submitted by Ramanjaneyulu K... on Sun, 12/06/2020 - 11:28

Dear sir,I am a student,I would like to work on this dataset to develop algorithms for Image Processing based on deep learning networks.

Submitted by yang yao on Sat, 03/27/2021 - 21:23

Dear sir,I am a student,I would like to work on this dataset to develop algorithms for Image Processing based on deep learning networks.

Submitted by Fan Xuenan on Sun, 09/04/2022 - 20:52

Dataset Files

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