Transformers in medical imaging: A survey
Following unprecedented success on the natural language tasks, Transformers have been
successfully applied to several computer vision problems, achieving state-of-the-art results …
successfully applied to several computer vision problems, achieving state-of-the-art results …
Recent advancement in cancer diagnosis using machine learning and deep learning techniques: A comprehensive review
D Painuli, S Bhardwaj - Computers in Biology and Medicine, 2022 - Elsevier
Being a second most cause of mortality worldwide, cancer has been identified as a perilous
disease for human beings, where advance stage diagnosis may not help much in …
disease for human beings, where advance stage diagnosis may not help much in …
Channel prior convolutional attention for medical image segmentation
H Huang, Z Chen, Y Zou, M Lu, C Chen, Y Song… - Computers in Biology …, 2024 - Elsevier
Characteristics such as low contrast and significant organ shape variations are often
exhibited in medical images. The improvement of segmentation performance in medical …
exhibited in medical images. The improvement of segmentation performance in medical …
An automated conversation system using natural language processing (nlp) chatbot in python
The purpose of this project is to build a ChatBot that utilises NLP (Natural Language
Processing) and assists customers. A ChatBot is an automated conversation system that …
Processing) and assists customers. A ChatBot is an automated conversation system that …
Big data and machine learning driven bioprocessing–recent trends and critical analysis
Given the potential of machine learning algorithms in revolutionizing the bioengineering
field, this paper examined and summarized the literature related to artificial intelligence (AI) …
field, this paper examined and summarized the literature related to artificial intelligence (AI) …
Cloud based iot smart healthcare system for remote patient monitoring
INTRODUCTION: Covid-19 has exposed the necessitate for the rapid acceptance of
increasingly pioneering digital health technologies, especially remote health monitoring …
increasingly pioneering digital health technologies, especially remote health monitoring …
An efficient Intra-Inter pixel encryption scheme to secure healthcare images for an IoT environment
Digital images are being frequently used for diagnosis in clinics today. Diagnostic images
with identifying patient data are stored and transmitted across open networks. Security …
with identifying patient data are stored and transmitted across open networks. Security …
Deep learning techniques for the classification of brain tumor: A comprehensive survey
Researchers have given immense consideration to unsupervised approaches because of
their tendency for automatic feature generation and excellent performance with a reduced …
their tendency for automatic feature generation and excellent performance with a reduced …
Application of belief functions to medical image segmentation: A review
The investigation of uncertainty is of major importance in risk-critical applications, such as
medical image segmentation. Belief function theory, a formal framework for uncertainty …
medical image segmentation. Belief function theory, a formal framework for uncertainty …
[PDF][PDF] Modified UNet Model for Brain Stroke Lesion Segmentation on Computed Tomography Images.
B Omarov, A Tursynova, O Postolache… - … Materials & Continua, 2022 - cdn.techscience.cn
The task of segmentation of brain regions affected by ischemic stroke is help to tackle
important challenges of modern stroke imaging analysis. Unfortunately, at the moment, the …
important challenges of modern stroke imaging analysis. Unfortunately, at the moment, the …