Academic Articles & Research Papers

Automated wound care by employing a reliable U-Net architecture combined with ResNet feature encoders for monitoring chronic wounds

Quality of life is greatly affected by chronic wounds. It requires more intensive care than acute wounds. Schedule follow-up appointments with their doctor to track healing. Good wound treatment promotes healing and fewer problems. Wound ca...

Volume Segmentation of Liver and Liver Tumor with Fusion of Multi-Branch Features

The overcomplete convolutional structure for biological images and volume segmentation is an excellent solution to the problem in which traditional codec methods cannot accurately segment the boundary regions. Although such methods perform ...

Decline in activities of daily living in the rarer dementias

Rarer dementias are associated with atypical symptoms and younger onset, which result in a higher burden of care. We provide a review of the global literature on longitudinal decline in activities of daily living (ADLs) in dementias that ac...

Mathematics and Visualization

Lipid Levels During Adult Lifetime in Men and Women With and Without a Subsequent Incident Myocardial Infarction: A Longitudinal Analysis of Data From the Tromsø Study 1974 to 2016

Background The atherosclerotic effect of an adverse lipid profile is assumed to accumulate throughout life, leading to increased risk of myocardial infarction (MI). Still, little is known about age at onset and duration of unfavorable lipid...

Longitudinal analysis of white matter and cortical lesions in multiple sclerosis

Purpose: The goals of this study were to assess the performance of a novel lesion segmentation tool for longitudinal analyses, as well as to validate the generated lesion progression map between two time points using conventional and non-co...

A Deep Learning Harmonization of Multi-Vendor MRI for Robust Intervertebral Disc Segmentation

Magnetic resonance imaging (MRI) provides enhanced soft tissue contrast and high spatial resolution. However, the relationship between intensity values among soft tissues in MRI is inconsistent, even when obtained under the same conditions ...

Fundus imaging based quantum computing: Grading of severity of vision threatening diabetic retinopathy

Diabetic Retinopathy (DR) is a major complication of diabetes that can result in irreversible vision loss if not detected early. Manual ophthalmologic screening is time-consuming and subject to subjectivity, underscoring the need for accura...

Using an Inspired Quantum-Classical Sequential Neural Network to Segment Liver Tumor Images Accurately

Medical analytics based on multimodal intelligence are essential to contemporary healthcare, especially in the diagnosis and detection of liver cancer. However, low contrast, varied textures, and irregular tumor forms in medical imaging con...

The state of quantum computing applications in health and medicine

Abstract Quantum computing hardware and software have made enormous strides over the last years1. Questions around quantum computing’s impact on research and society have changed from “if” to “when/how”. The 2020s have been described as the...

A survey of uncertainty in deep neural networks

Abstract Over the last decade, neural networks have reached almost every field of science and become a crucial part of various real world applications. Due to the increasing spread, confidence in neural network predictions has become more a...

Fuzzy logic and neural network handbook

Fuzzy logic principles and algorithms design guidelines for fuzzy logic systems enhanced training algorithms maximum likelihood training temporal difference learning NADINE hybrid learning systems explanation and reasoning within connectivi...

Potential of Radioactive Isotopes Production in DEMO for Commercial Use

There is widespread use of nuclear radiation for medical imagery and treatments. Worldwide, almost 40 million treatments are performed per year. There are also applications of radiation sources in other commercial fields, e.g., for weld ins...

Analyzing Brain Tumor Classification Techniques: A Comprehensive Survey

Classification of brain tumour is critical in medical image analysis and diagnosis as it aids in determining the affinity of cases to select treatment paths. This feature underscores the importance of accurate classification of brain tumour...

Exploring Deep Transfer Learning for Medical Image Processing and Analysis: A Comprehensive Analysis across Modalities.

TransCat: a hybrid CNN-transformer network with KAN for medical image segmentation

Medical image segmentation is a fundamental task in computer vision and plays an important role in clinical diagnosis and treatment planning. Existing methods are mainly built on either convolutional neural networks (CNNs) or Transformer-ba...

Computer Vision in Healthcare Applications

The research of computer vision, imaging processing and pattern recognition has made substantial progress during the past several decades.Also, medical imaging has attracted increasing attention in recent years due to its vital component in...

Enhancing medical image segmentation with HCE-Net: A heterogeneous feature collaborative extraction network.

Computer Vision for Biomedical Image Applications

Computer Vision and Pattern Recognition 2020

This special issue covers a wide range of topics from the area of Computer Vision, Pattern Recognition, and Machine Learning.This breadth of scope is reflected by the papers included in this special issue, which touch topics including geome...