Flexible endoscopes based on fiber bundles are still widely used despite the recent success of so-called tipchip endoscopes. This is partly due to the costs and that for extremely thin diameters (below 3 mm) there are still only fiberscopes available. Due to the inevitable artifacts caused by the transition from the fiber bundles to the sensor chip, image and texture analysis algorithms are severely handicapped. Therefore, texture-based computer-assisted diagnosis (CAD) systems could not be used in such domains without image preprocessing. We describe a CAD system approach that includes an image filtering algorithm to remove the fiber image artifacts first and then applies conventional color texture algorithms that have been applied to other endoscopic disciplines in the past. The concept is evaluated on an image database with artificially rendered fiber artifacts so that ground truth information is available.
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http://dx.doi.org/10.1109/IEMBS.2009.5334879 | DOI Listing |
Cell Physiol Biochem
December 2024
Joint Institute for Nuclear Research, 141980 Dubna, Russiac.
Background/aims: Alzheimer's Disease (AD) is a progressive neurodegenerative disorder that severely affects cognitive functions and memory. Early detection is crucial for timely intervention and improved patient outcomes. However, traditional diagnostic tools, such as MRI and PET scans, are costly and less accessible.
View Article and Find Full Text PDFComput Biol Med
January 2025
Information Technology Engineering Group, Department of Industrial Engineering, K.N. Toosi University of Technology, Tehran, Iran. Electronic address:
Breast mass segmentation plays a crucial role in early breast cancer detection and diagnosis, and while Convolutional Neural Networks (CNN) have been widely used for this task, their reliance on local receptive fields limits ability to capture long-range dependencies. Vision Transformers (ViTs), on the other hand, excel in this area by leveraging multi-head self-attention mechanisms to generate attention maps that dynamically gather global spatial information, significantly outperforming CNN-based architectures in various tasks. However, traditional transformer-based models come with challenges, including high computational complexity due to the self-attention mechanism and inefficiency in the static MLP fusion process.
View Article and Find Full Text PDFSci Rep
October 2024
Medical Image and Signal Processing Research Center, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
J Biophotonics
October 2024
Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, Illinois, USA.
Otitis media (OM), a highly prevalent inflammatory middle-ear disease in children worldwide, is commonly caused by an infection, and can lead to antibiotic-resistant bacterial biofilms in recurrent/chronic OM cases. A biofilm related to OM typically contains one or multiple bacterial species. OCT has been used clinically to visualize the presence of bacterial biofilms in the middle ear.
View Article and Find Full Text PDFPhys Med Biol
August 2024
Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, United States of America.
Simulation of positron emission tomography (PET) images is an essential tool in the development and validation of quantitative imaging workflows and advanced image processing pipelines. Existing Monte Carlo or analytical PET simulators often compromise on either efficiency or accuracy. We aim to develop and validate fast analytical simulator of tracer (FAST)-PET, a novel analytical framework, to simulate PET images accurately and efficiently.
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