Medical & biological engineering & computing
Jul 12, 2018
With the advent of biomedical imaging technology, the number of captured and stored biomedical images is rapidly increasing day by day in hospitals, imaging laboratories and biomedical institutions. Therefore, more robust biomedical image analysis te...
In this paper, we propose a method for automatically annotating slide images from colorectal tissue samples. Our objective is to segment glandular epithelium in histological images from tissue slides submitted to different staining techniques, includ...
Automation, machine learning, and artificial intelligence (AI) are changing the landscape of echocardiography providing complimentary tools to physicians to enhance patient care. Multiple vendor software programs have incorporated automation to impro...
IEEE journal of biomedical and health informatics
Jul 3, 2018
The level set based deformable models (LDM) are commonly used for medical image segmentation. However, they rely on a handcrafted curve evolution velocity that needs to be adapted for each segmentation task. The Convolutional Neural Networks (CNN) ad...
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Jun 29, 2018
Quantitative ultrasound (QUS) imaging methods, including elastography, echogenicity analysis, and speckle statistical modeling, are available from a single ultrasound (US) radio-frequency data acquisition. Since these US imaging methods provide compl...
Transplantable kidneys are in very limited supply. Accurate viability assessment prior to transplantation could minimize organ discard. Rapid and accurate evaluation of intra-operative donor kidney biopsies is essential for determining which kidneys ...
IEEE journal of biomedical and health informatics
Jun 25, 2018
Recent advances in deep learning have produced encouraging results for biomedical image segmentation; however, outcomes rely heavily on comprehensive annotation. In this paper, we propose a neural network architecture and a new algorithm, known as ov...
Temporal enhanced ultrasound (TeUS), comprising the analysis of variations in backscattered signals from a tissue over a sequence of ultrasound frames, has been previously proposed as a new paradigm for tissue characterization. In this paper, we prop...
Deep learning using convolutional neural networks (CNNs) is a distinguished tool for many image classification tasks. Due to its outstanding robustness and generalization, it is also expected to play a key role to facilitate advanced computer-aided d...
Nuclear alterations are a hallmark of many types of cancers, including prostate cancer (PCa). Recent evidence shows that subvisual changes, ones that may not be visually perceptible to a pathologist, to the nucleus and its ultrastructural components ...
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