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PPS: Semi-supervised 3D Biomedical Image Segmentation via Pyramid Pseudo-Labeling Supervision
Although deep learning models have demonstrated impressive performance in various biomedical image segmentation tasks, their effectiveness heavily...
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Use of Deep Learning in Biomedical Imaging
Biomedical imaging is one of the foremost tools for diagnosis support, treatment planning, disease progress assessment, and computer-assisted...
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Systematic Comparison of Incomplete-Supervision Approaches for Biomedical Image Classification
Deep learning based classification of biomedical images requires expensive manual annotation by experts. Incomplete-supervision approaches including...
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GLAN: GAN Assisted Lightweight Attention Network for Biomedical Imaging Based Diagnostics
Manual assessment of biomedical imaging based diagnostics is limited as it is time-consuming and subjective. Bio-inspired diagnostics applications on...
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Multimodal Biomedical Image Fusion Techniques in Transform and Spatial Domain: An Inclusive Survey
Image of similar object can be taken by using several modalities at same/different time and in various environmental conditions. The human perception...
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Traditional and deep-learning-based denoising methods for medical images
Visual information is extremely important in today’s world. Visual information transmitted in the form of digital images has become a critical mode...
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A New Similarity Metric for Deformable Registration of MALDI–MS and MRI Images
Multimodal imaging is a prominent strategy for biomedical research. For instance, Mass Spectrometry Imaging (MSI) can reveal the chemical composition...
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Gradient-Based Enhancement Attacks in Biomedical Machine Learning
The prevalence of machine learning in biomedical research is rapidly growing, yet the trustworthiness of such research is often overlooked. While...
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PMC-CLIP: Contrastive Language-Image Pre-training Using Biomedical Documents
Foundation models trained on large-scale dataset gain a recent surge in CV and NLP. In contrast, development in biomedical domain lags far behind due...
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Knowledge graph enrichment from clinical narratives using NLP, NER, and biomedical ontologies for healthcare applications
Electronic health records (EHR) contain patients’ health information in varied formats such as clinical reports written in natural language, X-rays,...
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Analysis and Classification of Biomedical and Bioinformation Systems Using a Generalized Spectral Analytical Approach
AbstractA generalized spectral analytical method is outlined—a new approach to processing information arrays. The theoretical foundations of the...
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Unsupervised Segmentation of High-Throughput Zebrafish Images Using Deep Neural Networks and Transformers
Zebrafish is a popular model system for biomedical analysis, especially for compound screening in drug research. In this paper, we present a...
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DM-Net: A Dual-Model Network for Automated Biomedical Image Diagnosis
Biomedical image segmentation is an essential task in the computer-aided diagnosis system. An encoder-decoder based on a shallow or deep...
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Signal Acquisition Preprocessing and Feature Extraction Techniques for Biomedical Signals
The primary purposes of the biomedical signals are the detection or diagnosis of disease or physiological states. These signals are also employed in...
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Learning-based and quality preserving super-resolution of noisy images
Purpose: Several applications require the super-resolution of noisy images and the preservation of geometrical and texture features. State-of-the-art...
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A Review of Predictive and Contrastive Self-supervised Learning for Medical Images
Over the last decade, supervised deep learning on manually annotated big data has been progressing significantly on computer vision tasks. But, the...
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Dfp-Unet: A Biomedical Image Segmentation Method Based on Deformable Convolution and Feature Pyramid
U-net is a classic deep network framework in the field of biomedical image segmentation, which uses a U-shaped encoder and decoder structure to...
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A colour image segmentation method and its application to medical images
In this paper, we propose a segmentation model using an anisotropic multi-well potential-based nonlinear transient PDE for colour images. A...
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Generalized gamma distribution for biomedical signals denoising
A wide range of signs are acquired from the human body called biomedical signs or biosignals, and they can be at the cell level, organ level, or...
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Compound Figure Separation of Biomedical Images with Side Loss
Unsupervised learning algorithms (e.g., self-supervised learning, auto-encoder, contrastive learning) allow deep learning models to learn effective...