SISE-PC: Semi-supervised Image Subsampling for Explainable Pathology

by   Sohini Roychowdhury, et al.

Although automated pathology classification using deep learning (DL) has proved to be predictively efficient, DL methods are found to be data and compute cost intensive. In this work, we aim to reduce DL training costs by pre-training a Resnet feature extractor using SimCLR contrastive loss for latent encoding of OCT images. We propose a novel active learning framework that identifies a minimal sub-sampled dataset containing the most uncertain OCT image samples using label propagation on the SimCLR latent encodings. The pre-trained Resnet model is then fine-tuned with the labelled minimal sub-sampled data and the underlying pathological sites are visually explained. Our framework identifies upto 2 prioritized specialist attention and that can fine-tune a Resnet model to achieve upto 97 to other medical images to minimize prediction costs.



There are no comments yet.


page 2

page 3

page 4


Unsupervised Deep Transfer Feature Learning for Medical Image Classification

The accuracy and robustness of image classification with supervised deep...

Self-supervised Mean Teacher for Semi-supervised Chest X-ray Classification

The training of deep learning models generally requires a large amount o...

Semi-supervised physics guided deep learning framework for predicting the I-V characteristics of GAN HEMT

This letter proposes a novel deep learning framework (DLF) that addresse...

Studying the Usage of Text-To-Text Transfer Transformer to Support Code-Related Tasks

Deep learning (DL) techniques are gaining more and more attention in the...

Deep Learning-Based Feature Extraction in Iris Recognition: Use Existing Models, Fine-tune or Train From Scratch?

Modern deep learning techniques can be employed to generate effective fe...

Deep Learning Face Attributes in the Wild

Predicting face attributes in the wild is challenging due to complex fac...

Improved TB classification using bone-suppressed chest radiographs

Chest X-rays (CXRs) are the most commonly performed diagnostic examinati...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.