Open Access. Powered by Scholars. Published by Universities.®
Bioimaging and Biomedical Optics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Keyword
-
- Breast Cancer (2)
- ADCN (1)
- Arrayed sensor (1)
- CT images (1)
- Chemical stimulation (1)
-
- Classification (1)
- Convolution neural network (1)
- Deep learning models (1)
- Doppler (1)
- Free-Space millimeter-wave measurements (1)
- Fringe projection profilometry (1)
- Gait Analysis (1)
- Graphene nanoplatelets (1)
- Hybrid convolution neural network. (1)
- Image Segmentation (1)
- K-means clustering (1)
- Liquid flow control (1)
- Liver segmentation (1)
- Local chemical delivery (1)
- Low voltage actuation (1)
- MPNET (1)
- Machine Learning (1)
- Macroporous silicon membrane (1)
- Material Characterization (1)
- Medical image analysis (1)
- Microwave and millimeter-wave measurements (1)
- Multispectral composite pattern (1)
- Non-Contact Techniques (1)
- Off-axis digital holographic interferometry (1)
- Optical 3D surface measurement. (1)
- Publication
- Publication Type
Articles 1 - 7 of 7
Full-Text Articles in Bioimaging and Biomedical Optics
Experimental And Analysis Of Electromagnetic Characterization Of Biological And Non-Biological Materials In Microwave, Millimeter-Wave, And Terahertz Frequency Bands, Nagma Vohra
Graduate Theses and Dissertations
The goal of this research is to characterize the electromagnetic properties of biological and non-biological materials at terahertz (THz), millimeter-wave, and microwave frequency bands. The biological specimens are measured using the THz imaging and spectroscopy system, whereas the non-biological materials are measured using the microwave and millimeter-wave free-space system. These facilities are located in the Engineering Research Center at the University of Arkansas. The THz imaging system (TPS 3000) uses a Ti-Sapphire laser directed on the photoconductive antennas to generate a THz time domain pulse. Upon using the Fourier Transform, the spectrum of the pulsed THz signal includes frequencies from …
Snapshot Three-Dimensional Surface Imaging With Multispectral Fringe Projection Profilometry, Parsa Omidi
Snapshot Three-Dimensional Surface Imaging With Multispectral Fringe Projection Profilometry, Parsa Omidi
Electronic Thesis and Dissertation Repository
Fringe Projection Profilometry (FPP) is a popular method for non-contact optical surface measurements, including motion tracking. The technique derives 3D surface maps from phase maps estimated from the distortions of fringe patterns projected onto the surface of an object. Estimation of phase maps is commonly performed with spatial phase retrieval algorithms that use a series of complex data processing stages. Researchers must have advanced data analysis skills to process FPP data due to a lack of availability of simple research-oriented software tools. Chapter 2 describes a comprehensive FPP software tool called PhaseWareTM that allows novice to experienced users to …
Non-Contact Techniques For Human Vital Sign Detection And Gait Analysis, Farnaz Foroughian
Non-Contact Techniques For Human Vital Sign Detection And Gait Analysis, Farnaz Foroughian
Doctoral Dissertations
Human vital signs including respiratory rate, heart rate, oxygen saturation, blood pressure, and body temperature are important physiological parameters that are used to track and monitor human health condition. Another important biological parameter of human health is human gait. Human vital sign detection and gait investigations have been attracted many scientists and practitioners in various fields such as sport medicine, geriatric medicine, bio-mechanic and bio-medical engineering and has many biological and medical applications such as diagnosis of health issues and abnormalities, elderly care and health monitoring, athlete performance analysis, and treatment of joint problems. Thoroughly tracking and understanding the normal …
Statistical Machine Learning For Breast Cancer Detection With Terahertz Imaging, Tanny Andrea Chavez Esparza
Statistical Machine Learning For Breast Cancer Detection With Terahertz Imaging, Tanny Andrea Chavez Esparza
Graduate Theses and Dissertations
Breast conserving surgery (BCS) is a common breast cancer treatment option, in which the cancerous tissue is excised while leaving most of the healthy breast tissue intact. The lack of in-situ margin evaluation unfortunately results in a re-excision rate of 20-30% for this type of procedure. This study aims to design statistical and machine learning segmentation algorithms for the detection of breast cancer in BCS by using terahertz (THz) imaging. Given the material characterization properties of the non-ionizing radiation in the THz range, we intend to employ the responses from the THz system to identify healthy and cancerous breast tissue …
Development Of Light Actuated Chemical Delivery Platform On A 2-D Array Of Micropore Structure, Hojjat Rostami Azmand, Hojjat Rostami Azmand
Development Of Light Actuated Chemical Delivery Platform On A 2-D Array Of Micropore Structure, Hojjat Rostami Azmand, Hojjat Rostami Azmand
Dissertations and Theses
Localized chemical delivery plays an essential role in the fundamental information transfers within biological systems. Thus, the ability to mimic the natural chemical signal modulation would provide significant contributions to understand the functional signaling pathway of biological cells and develop new prosthetic devices for neurological disorders. In this paper, we demonstrate a light-controlled hydrogel platform that can be used for localized chemical delivery in a high spatial resolution. By utilizing the photothermal behavior of graphene-hydrogel composites confined within micron-sized fluidic channels, patterned light illumination creates the parallel and independent actuation of chemical release in a group of fluidic ports. The …
Bibliometric Review On Applications Of Disease Detection Using Digital Image Processing Techniques, Jayant Jagtap, Rahil Sharma, Aryan Sinha, Nikhil Panda, Amulya Reddy
Bibliometric Review On Applications Of Disease Detection Using Digital Image Processing Techniques, Jayant Jagtap, Rahil Sharma, Aryan Sinha, Nikhil Panda, Amulya Reddy
Library Philosophy and Practice (e-journal)
Advances around the field of deep learning and cognitive computing have allowed mankind to look and solve the problems of the world in a completely new way. Deep learning has been making huge advancements in the field of healthcare, which most importantly focuses upon disease detection and disease prediction. Techniques such as these have been conceptualized the idea of early detection and economical ways of treating the predicted disease in particular. Still, it has been observed that there seems to be no change in the way diagnosis of a particular disease takes place even in the 21st generation of …
Bibliometric Review On Liver And Tumour Segmentation Using Deep Learning, Jayant Jagtap, Aamir Habeeb, Avinash Jha, Shrey Aggarwal, Khushi Gupta
Bibliometric Review On Liver And Tumour Segmentation Using Deep Learning, Jayant Jagtap, Aamir Habeeb, Avinash Jha, Shrey Aggarwal, Khushi Gupta
Library Philosophy and Practice (e-journal)
One of the major organs in the body is liver where tumors occur often. Malignant liver tumors pose a serious hazard to human life and health. Manual segmentation of the liver organ and tumor from computed tomography (CT) scans is difficult, time-consuming, and skewed to the clinician's experience, yet it is essential for hepatic surgical planning. However, due to the following considerations, segmenting liver tumors from computed tomography (CT) images is difficult: In CT pictures, the contrast between the liver tumor and healthy tissues is low, and the boundary is indistinct; the picture of the liver tumor is confusing, with …