scholarly journals Siamese Networks With Location Prior for Landmark Tracking in Liver Ultrasound Sequences

2019 ◽  
Author(s):  
Alvaro Gomariz ◽  
Weiye Li ◽  
Ece Ozkan ◽  
Christine Tanner ◽  
Orcun Goksel
Keyword(s):  
Liver Ultrasound ◽  
Landmark Tracking ◽  
Siamese Networks

RISK FACTORS IN THE DEVELOPMENT OF LIVER ABSCESSES AND DIAGNOSTIC STRATEGY IN THEIR SUSPECTED PRESENCE

2016 ◽  
Vol 2 (1) ◽  
pp. 31
Author(s):  
Josiah Iju WILSON ◽  
Vladimir Egorovich MEDVEDEV
Keyword(s):  
Risk Factors ◽  
Clinical Laboratory ◽  
Inflammatory Diseases ◽  
Bacterial Overgrowth ◽  
Diagnostic Strategy ◽  
Hydrogen Breath Test ◽  
Severe Condition ◽  
Liver Ultrasound ◽  
Liver Abscesses ◽  
History Of

Introduction: The main risk aetiological factors of liver abscesses and development of precision liver ultrasound recommendations to detect signs of possible abscess formation were studied.Material and methods: 248 patients of both sexes aged 4-81 years with liver abscesses were analyzed. Medical history, physical examination, clinical laboratory tests, hydrogen breath test with, ultrasound examination, if necessary - computed tomography and fine needle diagnostic biopsy under ultrasound guidance were carried out..Results and discussion: It was established that liver abscesses are aetiologically heterogeneous, in which the largest in the group was pylephlebitic (64.1%), posttraumatic (14.5%), cholangiogenic (12.5%) and contact abscesses (1.2 %). In connection with the effacement or nonspecific clinical picture, often severe condition of the patient, the prevalence of symptoms in some cases of other diseases, liver abscesses may not be promptly diagnosed.Conclusion: The presence of clinical and laboratory signs of suppurate inflammatory processes, risk factors such as the presence of bacterial overgrowth syndrome, inflammatory diseases of the intestines, history of the use of proton pump inhibitors, diseases in association with cholestasis, surgery, history of trauma, abscesses of other locations, it is recommended that precision liver ultrasound should be carried out to detect possible echo signs of liver abscesses.

scholarly journals Using extended siamese networks to provide decision support in aquaculture operations

2021 ◽  
Author(s):  
Bjørn Magnus Mathisen ◽  
Kerstin Bach ◽  
Agnar Aamodt
Keyword(s):  
Neural Networks ◽  
Decision Support ◽  
Similar Case ◽  
Decision Makers ◽  
Similarity Function ◽  
Case Based Reasoning ◽  
Similarity Learning ◽  
Reasoning System ◽  
Siamese Networks ◽  
Case Based

AbstractAquaculture as an industry is quickly expanding. As a result, new aquaculture sites are being established at more exposed locations previously deemed unfit because they are more difficult and resource demanding to safely operate than are traditional sites. To help the industry deal with these challenges, we have developed a decision support system to support decision makers in establishing better plans and make decisions that facilitate operating these sites in an optimal manner. We propose a case-based reasoning system called aquaculture case-based reasoning (AQCBR), which is able to predict the success of an aquaculture operation at a specific site, based on previously applied and recorded cases. In particular, AQCBR is trained to learn a similarity function between recorded operational situations/cases and use the most similar case to provide explanation-by-example information for its predictions. The novelty of AQCBR is that it uses extended Siamese neural networks to learn the similarity between cases. Our extensive experimental evaluation shows that extended Siamese neural networks outperform state-of-the-art methods for similarity learning in this task, demonstrating the effectiveness and the feasibility of our approach.

scholarly journals Association Between Transient Elastography and Controlled Attenuated Parameter and Liver Ultrasound in Children With Cystic Fibrosis

2021 ◽  
Author(s):  
Wen Ye ◽  
Daniel H. Leung ◽  
Jean P. Molleston ◽  
Simon C. Ling ◽  
Karen F. Murray ◽  
...  
Keyword(s):  
Cystic Fibrosis ◽  
Transient Elastography ◽  
Liver Ultrasound

scholarly journals Experiments of Image Classification Using Dissimilarity Spaces Built with Siamese Networks

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1573
Author(s):  
Loris Nanni ◽  
Giovanni Minchio ◽  
Sheryl Brahnam ◽  
Gianluca Maguolo ◽  
Alessandra Lumini
Keyword(s):  
Vector Space ◽  
Image Classification ◽  
Ad Hoc ◽  
Feature Space ◽  
Medical Data ◽  
Training Data ◽  
Data Sets ◽  
Large Set ◽  
Clustering Methods ◽  
Siamese Networks

Traditionally, classifiers are trained to predict patterns within a feature space. The image classification system presented here trains classifiers to predict patterns within a vector space by combining the dissimilarity spaces generated by a large set of Siamese Neural Networks (SNNs). A set of centroids from the patterns in the training data sets is calculated with supervised k-means clustering. The centroids are used to generate the dissimilarity space via the Siamese networks. The vector space descriptors are extracted by projecting patterns onto the similarity spaces, and SVMs classify an image by its dissimilarity vector. The versatility of the proposed approach in image classification is demonstrated by evaluating the system on different types of images across two domains: two medical data sets and two animal audio data sets with vocalizations represented as images (spectrograms). Results show that the proposed system’s performance competes competitively against the best-performing methods in the literature, obtaining state-of-the-art performance on one of the medical data sets, and does so without ad-hoc optimization of the clustering methods on the tested data sets.

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