Brain Tumor Image DataSet: Instance Segmentation

Brain Tumor Image DataSet: Instance Segmentation

Datasets

Brain Tumor Image DataSet: Instance Segmentation

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Brain Tumor Image DataSet: Instance Segmentation

Use Case

Computer Vision

Description

The Tumor Detection Dataset is a specialized dataset intended for a Computer Vision Project that focuses on Instance Segmentation.

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About Dataset

Tumor Detection Dataset: Instance Segmentation

This Tumor Detection Dataset is made for a special Computer Vision Project that’s all about spotting tumors in medical images. The main goal of the project is to find and outline tumor areas in these images, which is really useful for diagnosing illnesses. This dataset is quite recent, last updated about 9 months back, showing that it’s still really important and up-to-date in the world of computer vision.

Details of the Dataset:

Project Type: Instance Segmentation
Subject: Tumor
Classes:

Tumor_Good_Chance
Tumor_Less_Chance
Tumor_Moderate_Chance

Project Overview:

The project associated with this dataset is focused on employing sophisticated instance segmentation methods to tackle tumor detection in medical images. Instance segmentation goes beyond merely spotting tumors; it also entails precisely outlining their boundaries within the images. This meticulous level of analysis is essential for medical experts to evaluate the characteristics and seriousness of tumors.

Classes:

The dataset is divided into three categories, each indicating varying probabilities or levels of tumor presence. These categories, namely Tumor_Good_ChanceTumor_Less_Chance, and Tumor_Moderate_Chance, enable a detailed understanding of the identified tumors based on their likelihood or severity.

 

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