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Omni-dimensional dynamic convolution feature coordinate attention network for pneumonia classification
Pneumonia is a serious disease that can be fatal, particularly among children and the elderly. The accuracy of pneumonia diagnosis can be improved by...
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Non-invasively identifying candidates of active surveillance for prostate cancer using magnetic resonance imaging radiomics
Active surveillance (AS) is the primary strategy for managing patients with low or favorable-intermediate risk prostate cancer (PCa). Identifying...
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Two-step hierarchical binary classification of cancerous skin lesions using transfer learning and the random forest algorithm
Skin lesion classification plays a crucial role in the early detection and diagnosis of various skin conditions. Recent advances in computer-aided...
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Parallel processing model for low-dose computed tomography image denoising
Low-dose computed tomography (LDCT) has gained increasing attention owing to its crucial role in reducing radiation exposure in patients. However,...
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Simulated deep CT characterization of liver metastases with high-resolution filtered back projection reconstruction
Early diagnosis and accurate prognosis of colorectal cancer is critical for determining optimal treatment plans and maximizing patient outcomes,...
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Schlieren imaging and video classification of alphabet pronunciations: exploiting phonetic flows for speech recognition and speech therapy
Speech is a highly coordinated process that requires precise control over vocal tract morphology/motion to produce intelligible sounds while...
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V4RIN: visual analysis of regional industry network with domain knowledge
The regional industry network (RIN) is a type of financial network derived from industry networks that possess the capability to describe the...
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Typicality- and instance-dependent label noise-combating: a novel framework for simulating and combating real-world noisy labels for endoscopic polyp classification
Learning with noisy labels aims to train neural networks with noisy labels. Current models handle instance-independent label noise (IIN) well;...
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Dual modality prompt learning for visual question-grounded answering in robotic surgery
With recent advancements in robotic surgery, notable strides have been made in visual question answering (VQA). Existing VQA systems typically...
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Automated analysis of pectoralis major thickness in pec-fly exercises: evolving from manual measurement to deep learning techniques
This study addresses a limitation of prior research on pectoralis major (PMaj) thickness changes during the pectoralis fly exercise using a wearable...
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Three-dimensional reconstruction of industrial parts from a single image
This study proposes an image-based three-dimensional (3D) vector reconstruction of industrial parts that can generate non-uniform rational B-splines...
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PlaqueNet: deep learning enabled coronary artery plaque segmentation from coronary computed tomography angiography
Cardiovascular disease, primarily caused by atherosclerotic plaque formation, is a significant health concern. The early detection of these plaques...
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Flipover outperforms dropout in deep learning
Flipover, an enhanced dropout technique, is introduced to improve the robustness of artificial neural networks. In contrast to dropout, which...
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Convolutional neural network based data interpretable framework for Alzheimer’s treatment planning
Alzheimer’s disease (AD) is a neurological disorder that predominantly affects the brain. In the coming years, it is expected to spread rapidly, with...
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Multi-task approach based on combined CNN-transformer for efficient segmentation and classification of breast tumors in ultrasound images
Nowadays, inspired by the great success of Transformers in Natural Language Processing, many applications of Vision Transformers (ViTs) have been...
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CT-based radiomics: predicting early outcomes after percutaneous transluminal renal angioplasty in patients with severe atherosclerotic renal artery stenosis
This study aimed to comprehensively evaluate non-contrast computed tomography (CT)-based radiomics for predicting early outcomes in patients with...
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A Comparison of Hosting Techniques for Online Cybersecurity Competitions
Online cybersecurity competitions have gained significant traction in the community for educational and evaluative purposes because they offer...
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Advancing Multi-actor Graph Convolutions for Skeleton-Based Action Recognition
Human skeleton motion recognition, notable for its lightweight, interference-resistant, and resource-saving properties, plays a crucial role in human...
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A Somaesthetics Based Approach to the Design of Multisensory Interactive Systems
This paper aims to analyse the state-of-the-art of somaesthetics, describing the scientific and philosophic basis of the discipline, in order to...