Recent progress in transformer-based medical image analysis
The transformer is primarily used in the field of natural language processing. Recently, it has
been adopted and shows promise in the computer vision (CV) field. Medical image analysis …
been adopted and shows promise in the computer vision (CV) field. Medical image analysis …
A survey of the impact of self-supervised pretraining for diagnostic tasks in medical X-ray, CT, MRI, and ultrasound
Self-supervised pretraining has been observed to be effective at improving feature
representations for transfer learning, leveraging large amounts of unlabelled data. This …
representations for transfer learning, leveraging large amounts of unlabelled data. This …
[HTML][HTML] Self-supervised adversarial adaptation network for breast cancer detection
Breast cancer is the most commonly diagnosed cancer worldwide, and early detection is
essential for reducing mortality rates. Digital mammography is currently the best standard for …
essential for reducing mortality rates. Digital mammography is currently the best standard for …
A survey of the impact of self-supervised pretraining for diagnostic tasks with radiological images
Self-supervised pretraining has been observed to be effective at improving feature
representations for transfer learning, leveraging large amounts of unlabelled data. This …
representations for transfer learning, leveraging large amounts of unlabelled data. This …
Self-Supervised Bi-Pipeline Learning Approach for High Interpretation of Breast Thermal Images
The image quality supports a high accuracy rate of medical image diagnosis using computer
vision. Digital thermal images resulting from the thermal device usually suffer from many …
vision. Digital thermal images resulting from the thermal device usually suffer from many …
[PDF][PDF] Knowledge-Guided Self-Supervised Vision Transformers for Medical Imaging
Recent trends in self-supervised representation learning have focused on removing
inductive biases from the training process. However, inductive biases can be useful in …
inductive biases from the training process. However, inductive biases can be useful in …
[PDF][PDF] Object-Level Representation Learning for Natural and Medical Images
A Gokul - 2022 - digicoll.lib.berkeley.edu
Object perception and recognition is a fundamental part of visual scene understanding.
Humans, even as young as infants, possess a remarkable ability to perceive and represent …
Humans, even as young as infants, possess a remarkable ability to perceive and represent …
Equipment identification through image recognition
D Saidnassimov - 2022 - aaltodoc.aalto.fi
Object detection is a rapidly-evolving field with applications varying from medicine to self-
driving vehicles. As the performance of the deep learning algorithms grow exponentially …
driving vehicles. As the performance of the deep learning algorithms grow exponentially …
A Review on “Efficient Hybrid Methodology for Early Detection of Breast Cancer in Digital Mammograms using Autoencoder Deep Learning”
AR Dankekar, A Sharma, J Mishra - Recent Advances in Science … - taylorfrancis.com
The most prevalent form of cancer in humans is breast cancer. The term cancer was first
used to describe the illness in Egypt around 1600 BC. Despite the fact that since then …
used to describe the illness in Egypt around 1600 BC. Despite the fact that since then …