Deep Medical Image Analysis with Representation Learning and Neuromorphic Computing

05/11/2020
by   Neil Getty, et al.
0

We explore three representative lines of research and demonstrate the utility of our methods on a classification benchmark of brain cancer MRI data. First, we present a capsule network that explicitly learns a representation robust to rotation and affine transformation. This model requires less training data and outperforms both the original convolutional baseline and a previous capsule network implementation. Second, we leverage the latest domain adaptation techniques to achieve a new state-of-the-art accuracy. Our experiments show that non-medical images can be used to improve model performance. Finally, we design a spiking neural network trained on the Intel Loihi neuromorphic chip (Fig. 1 shows an inference snapshot). This model consumes much lower power while achieving reasonable accuracy given model reduction. We posit that more research in this direction combining hardware and learning advancements will power future medical imaging (on-device AI, few-shot prediction, adaptive scanning).

READ FULL TEXT

page 1

page 2

page 5

research
07/19/2018

Capsule Networks against Medical Imaging Data Challenges

A key component to the success of deep learning is the availability of m...
research
05/19/2022

3DConvCaps: 3DUnet with Convolutional Capsule Encoder for Medical Image Segmentation

Convolutional Neural Networks (CNNs) have achieved promising results in ...
research
06/06/2022

Implementation of a Modified U-Net for Medical Image Segmentation on Edge Devices

Deep learning techniques, particularly convolutional neural networks, ha...
research
02/25/2017

Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation

Magnetic Resonance Imaging (MRI) is widely used in routine clinical diag...
research
02/27/2018

Brain Tumor Type Classification via Capsule Networks

Brain tumor is considered as one of the deadliest and most common form o...
research
01/10/2020

Diagnosing Colorectal Polyps in the Wild with Capsule Networks

Colorectal cancer, largely arising from precursor lesions called polyps,...
research
06/07/2018

Nonparametric Density Flows for MRI Intensity Normalisation

With the adoption of powerful machine learning methods in medical image ...

Please sign up or login with your details

Forgot password? Click here to reset