scholarly journals Translational Photoacoustic Imaging for Disease Diagnosis, Monitoring, and Surgical Guidance: Introduction to Feature Issue

2021 ◽  
Author(s):  
Jun Xia
Keyword(s):  
Photoacoustic Imaging ◽  
Disease Diagnosis ◽  
Surgical Guidance

scholarly journals Hyperspectral Imaging for Clinical Applications

2022 ◽  
Author(s):  
Jonghee Yoon
Keyword(s):  
Hyperspectral Imaging ◽  
Fluorescent Dyes ◽  
Disease Diagnosis ◽  
Clinical Applications ◽  
Optical Systems ◽  
Clinical Implementation ◽  
Significant Information ◽  
Surgical Guidance ◽  
Guided Surgery ◽  
Clinically Significant

AbstractMeasuring morphological and biochemical features of tissue is crucial for disease diagnosis and surgical guidance, providing clinically significant information related to pathophysiology. Hyperspectral imaging (HSI) techniques obtain both spatial and spectral features of tissue without labeling molecules such as fluorescent dyes, which provides rich information for improved disease diagnosis and treatment. Recent advances in HSI systems have demonstrated its potential for clinical applications, especially in disease diagnosis and image-guided surgery. This review summarizes the basic principle of HSI and optical systems, deep-learning-based image analysis, and clinical applications of HSI to provide insight into this rapidly growing field of research. In addition, the challenges facing the clinical implementation of HSI techniques are discussed.

scholarly journals Photoacoustic imaging for surgical guidance: Principles, applications, and outlook

2020 ◽  
Vol 128 (6) ◽  
pp. 060904 ◽  
Author(s):  
Muyinatu A. Lediju Bell
Keyword(s):  
Photoacoustic Imaging ◽  
Surgical Guidance

A Novel Hyperspectral Endoscopic Imaging Method Based on Broad- and Overlapped-Band Filters

2017 ◽  
Author(s):  
Zhimin Han ◽  
Tianyu Xie ◽  
Aoyu Zhang
Keyword(s):  
Optical Filters ◽  
Disease Diagnosis ◽  
Imaging Method ◽  
High Exposure ◽  
Surgical Guidance ◽  
Colon Biopsy ◽  
Research Problems ◽  
Medical Domain ◽  
Charged Couple Device

In medical domain, hyperspectral imaging (HSI) [1] offers a hybrid modality of optical diagnostics that obtains spectral information and renders the information in image form, thus it has great potential for noninvasive disease diagnosis and surgical guidance [2]. Masood [3] explored a series of research problems for classification of hyperspectral (HS) colon biopsy images, and concluded that HSI has enough discriminatory power to distinguish normal and malignant biopsy tissues. However, HS illumination is always with low intensity and signal-to-noise (SNR) ratio is low for HS images. The reason is that sensors of endoscopic systems, such as charged-couple-device (CCD), work by converting photons into electrons which are then stored in each pixel. The number of electrons stored in each pixel well is proportional to the number of photons that struck that pixel, although in actual pixel well, electrons are not only generated when receiving photons, but also due to physical processes within CCD itself, such as thermal noise which generates additional electrons dependent to temperature [4,5]. At the same time, dispersive device such as monochromators (such as prism and grating), and optical filters (including interference filters and tunable filters) are commonly used for HS imaging. Using these traditional filtering approaches, only a low fractions of photons are transmitted into the sensor. Moreover, due to the requirements of safety and keeping the working time per frame as short as possible for in-vivo and real-time application in medical domain, common methods which could improve SNR, such as using cooled sensor or high exposure time, are not applicable for HS endoscopy systems. To overcome this drawback, we proposed this novel HS imaging method based on broad- and overlapped-band filters [6].

Use of TEM in Plant Disease Diagnosis: A Xylem-Limited Bacterium Associated with Diseased ‘Toronto’ Creeping Bentgrass

1981 ◽  
Vol 39 ◽  
pp. 414-415
Author(s):  
Karen K. Baker ◽  
David L. Roberts
Keyword(s):  
Osmium Tetroxide ◽  
Plant Disease ◽  
Leaf Tissue ◽  
Infectious Agent ◽  
Creeping Bentgrass ◽  
Disease Diagnosis ◽  
Unknown Etiology ◽  
Agrostis Palustris ◽  
Putting Greens ◽  
Plant Disease Diagnosis

Plant disease diagnosis is most often accomplished by examination of symptoms and observation or isolation of causal organisms. Occasionally, diseases of unknown etiology occur and are difficult or impossible to accurately diagnose by the usual means. In 1980, such a disease was observed on Agrostis palustris Huds. c.v. Toronto (creeping bentgrass) putting greens at the Butler National Golf Course in Oak Brook, IL.The wilting symptoms of the disease and the irregular nature of its spread through affected areas suggested that an infectious agent was involved. However, normal isolation procedures did not yield any organism known to infect turf grass. TEM was employed in order to aid in the possible diagnosis of the disease.Crown, root and leaf tissue of both infected and symptomless plants were fixed in cold 5% glutaraldehyde in 0.1 M phosphate buffer, post-fixed in buffered 1% osmium tetroxide, dehydrated in ethanol and embedded in a 1:1 mixture of Spurrs and epon-araldite epoxy resins.

An Immunoradiometric Assay for Factor VIII Related Antigen (VIIIRAg) Using Two Monoclonal Antibodies-Comparison with Polyclonal Rabbit Antibodies for Use in von Willebrand’s Disease Diagnosis

1984 ◽  
Vol 52 (03) ◽  
pp. 250-252 ◽  
Author(s):  
Y Sultan ◽  
Ph Avner ◽  
P Maisonneuve ◽  
D Arnaud ◽  
Ch Jeanneau
Keyword(s):  
Monoclonal Antibodies ◽  
Structural Changes ◽  
Polyclonal Antibodies ◽  
Disease Diagnosis ◽  
Immunoradiometric Assay ◽  
Von Willebrand's Disease ◽  
Von Willebrand’S Disease ◽  
Structural Abnormalities ◽  
Antigenic Material ◽  
Von Willebrand

SummaryTwo monoclonal antibodies raised against FVIII/von Willebrand protein were used in an immunoradiometric assay (IRMA) to measure this antigen in normal plasma and plasma of patients with different forms of von Willebrand’s disease. The first antibody, an IgG1 was used to coat polystyrene tubes, the second one, an IgG2a, iodinated and used in the second step. Both antibodies inhibit ristocetin induced platelet agglutination and react strongly with platelets, megacaryocytes and endothelial cells. The IRMA test using these antibodies showed greater sensitivity than that using rabbit polyclonal anti VIIIRAg antibodies. A good correlation between the two tests was nevertheless found when VIIIRAg was measured in the majority of patient’s plasma. However 5 patients from 3 different families showed more antigenic material in the rabbit antibody IRMA than in the monoclonal antibody IRMA. It is suggested therefore that the monoclonal antibodies identify part of the VIIIR:Ag molecule showing structural abnormalities in these vWd patients, these structural changes remaining undetected by the polyclonal antibodies.

Síndrome da Anca de Ressalto

2018 ◽  
Vol 9 (1) ◽  
pp. 8
Author(s):  
Bernardo Almeida
Keyword(s):  
Surgical Treatment ◽  
Hip Joint ◽  
Scientific Literature ◽  
Therapeutic Targets ◽  
Clinical History ◽  
Disease Diagnosis ◽  
Diagnosis And Treatment ◽  
Snapping Hip ◽  
Predominant Symptom ◽  
Snapping Hip Syndrome

Snapping hip syndrome is a condition in which the predominant symptom is the snapping feelingaround the hip joint caused by a dynamic impingement between muscles or tendons and boneprominences. The etiology of the snapping hip types and consequently the therapeutic targets havebeen subjects of discussion and controversy along the years. A careful clinical history and physicalexamination is frequently enough for this disease diagnosis. Treatment is typically conservative,however when it is not successful surgical treatment is indicated, consisting on the snapping muscleor tendons lengthening. The authors review in this paper the current scientific literature about functionalanatomy, physiopathology, symptoms, diagnosis and treatment of snapping hip.

Machine Learning in Agriculture

2018 ◽  
Vol 8 (6) ◽  
pp. 26 ◽  
Author(s):  
Matthew N. O. Sadiku ◽  
Chandra M. M Kotteti ◽  
Sarhan M. Musa
Keyword(s):  
Climate Change ◽  
Artificial Intelligence ◽  
Machine Learning ◽  
Disease Diagnosis ◽  
Automated Detection ◽  
Disease Prediction ◽  
Paper Briefly ◽  
Agriculture Sector ◽  
Modern Agriculture ◽  
Crop Disease

Machine learning is an emerging field of artificial intelligence which can be applied to the agriculture sector. It refers to the automated detection of meaningful patterns in a given data.  Modern agriculture seeks ways to conserve water, use nutrients and energy more efficiently, and adapt to climate change.  Machine learning in agriculture allows for more accurate disease diagnosis and crop disease prediction. This paper briefly introduces what machine learning can do in the agriculture sector.

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