We present a portable multi-contrast microscope capable of producing bright-field, dark-field, and differential phase contrast images of thin biological specimens on a smartphone platform. The microscopy method is based on an imaging scheme termed "color-coded light-emitting-diode (LED) microscopy (cLEDscope)," in which a specimen is illuminated with a color-coded LED array and light transmitted through the specimen is recorded by a color image sensor. Decomposition of the image into red, green, and blue colors and subsequent computation enable multi-contrast imaging in a single shot. In order to transform a smartphone into a multi-contrast imaging device, we developed an add-on module composed of a patterned color micro-LED array, specimen stage, and miniature objective. Simple installation of this module onto a smartphone enables multi-contrast imaging of transparent specimens. In addition, an Android-based app was implemented to acquire an image, perform the associated computation, and display the multi-contrast images in real time. Herein, the details of our smartphone module and experimental demonstrations with various biological specimens are presented.
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http://dx.doi.org/10.1038/s41598-017-07703-w | DOI Listing |
Virtual Real
December 2024
Department of Computer Science and Software Engineering, Concordia University, Montreal, Québec Canada.
Epilepsy is a neurological disorder characterized by recurring seizures that can cause a wide range of symptoms. Stereo-electroencephalography (SEEG) is a diagnostic procedure where multiple electrodes are stereotactically implanted within predefined brain regions to identify the seizure onset zone, which needs to be surgically removed or disconnected to achieve remission of focal epilepsy. This procedure is complex and challenging due to two main reasons.
View Article and Find Full Text PDFJ Med Imaging (Bellingham)
December 2024
University of Houston, Department of Physics, Houston, Texas, United States.
Purpose: Photon counting detectors offer promising advancements in computed tomography (CT) imaging by enabling the quantification and three-dimensional imaging of contrast agents and tissue types through simultaneous multi-energy projections from broad X-ray spectra. However, the accuracy of these decomposition methods hinges on precise composite spectral attenuation values that one must reconstruct from spectral micro-CT. Errors in such estimations could be due to effects such as beam hardening, object scatter, or detector sensor-related spectral distortions such as fluorescence.
View Article and Find Full Text PDFMed Phys
December 2024
Jiangsu Key Laboratory for Biomaterials and Devices, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China.
Background: Medical imaging plays a pivotal role in the real-time monitoring of patients during the diagnostic and therapeutic processes. However, in clinical scenarios, the acquisition of multi-modal imaging protocols is often impeded by a number of factors, including time and economic costs, the cooperation willingness of patients, imaging quality, and even safety concerns.
Purpose: We proposed a learning-based medical image synthesis method to simplify the acquisition of multi-contrast MRI.
medRxiv
December 2024
Department of Bioengineering, University of Washington, Seattle, WA, USA.
Background: Carotid atherosclerosis is a major etiology of stroke. Although intraplaque hemorrhage (IPH) is known to increase stroke risk and plaque burden, its long-term effects on plaque dynamics remain unclear.
Objectives: This study aimed to evaluate the long-term impact of IPH on carotid plaque burden progression using deep learning-based segmentation on multi-contrast vessel wall imaging (VWI).
Magn Reson Imaging
December 2024
Department of Electronic Information Engineering, Nanchang University, Nanchang 330031, China. Electronic address:
Purpose: Multi-contrast magnetic resonance imaging is a significant and essential medical imaging technique. However, multi-contrast imaging has longer acquisition time and is easy to cause motion artifacts. In particular, the acquisition time for a T2-weighted image is prolonged due to its longer repetition time (TR).
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