metadata
license: apache-2.0
tags:
- brain-mri
- segmentation
- medical-imaging
- deep-learning
- unet
base_model: tf-keras/imagenet-mobilenetv2
model-index:
- name: Brain MRI Segmentation - FLAIR Abnormality Segmentation
results:
- task:
type: image-segmentation
name: Image Segmentation
dataset:
name: LGG Segmentation Dataset
type: medical-imaging
link: https://www.kaggle.com/datasets/mateuszbuda/lgg-mri-segmentation
metrics:
- type: dice
value: 0.843
name: Dice Coefficient
- type: iou
value: 0.609
name: Intersection over Union (IoU)
Brain MRI Segmentation - FLAIR Abnormality Segmentation v1.0.0
This repository hosts the trained model for FLAIR Abnormality Segmentation in Brain MRI scans. The model is a U-Net architecture with a MobileNetV2 encoder pretrained on ImageNet, designed to segment FLAIR abnormalities from MRI images effectively.
Model Details
- Architecture: U-Net with MobileNetV2 encoder and custom decoder layers.
- Dataset: LGG Segmentation Dataset
- Version: v1.0.0
- Task: Image Segmentation
- License: Apache 2.0