A Novel Domain Adaptation Framework for Medical Image Segmentation

by   Amir Gholami, et al.

We propose a segmentation framework that uses deep neural networks and introduce two innovations. First, we describe a biophysics-based domain adaptation method. Second, we propose an automatic method to segment white and gray matter, and cerebrospinal fluid, in addition to tumorous tissue. Regarding our first innovation, we use a domain adaptation framework that combines a novel multispecies biophysical tumor growth model with a generative adversarial model to create realistic looking synthetic multimodal MR images with known segmentation. Regarding our second innovation, we propose an automatic approach to enrich available segmentation data by computing the segmentation for healthy tissues. This segmentation, which is done using diffeomorphic image registration between the BraTS training data and a set of prelabeled atlases, provides more information for training and reduces the class imbalance problem. Our overall approach is not specific to any particular neural network and can be used in conjunction with existing solutions. We demonstrate the performance improvement using a 2D U-Net for the BraTS'18 segmentation challenge. Our biophysics based domain adaptation achieves better results, as compared to the existing state-of-the-art GAN model used to create synthetic data for training.


Augmentation based unsupervised domain adaptation

The insertion of deep learning in medical image analysis had lead to the...

Domain Adaptation: the Key Enabler of Neural Network Equalizers in Coherent Optical Systems

We introduce the domain adaptation and randomization approach for calibr...

SynthMix: Mixing up Aligned Synthesis for Medical Cross-Modality Domain Adaptation

The adversarial methods showed advanced performance by producing synthet...

The Domain Shift Problem of Medical Image Segmentation and Vendor-Adaptation by Unet-GAN

Convolutional neural network (CNN), in particular the Unet, is a powerfu...

Development of an algorithm for medical image segmentation of bone tissue in interaction with metallic implants

This preliminary study focuses on the development of a medical image seg...

Domain Adaptation with Morphologic Segmentation

We present a novel domain adaptation framework that uses morphologic seg...

Using Out-of-the-Box Frameworks for Unpaired Image Translation and Image Segmentation for the crossMoDA Challenge

The purpose of this study is to apply and evaluate out-of-the-box deep l...

Please sign up or login with your details

Forgot password? Click here to reset