Tissue Differentiation Based on Classification of Morphometric Features of Nuclei

2020 ◽  
pp. 420-432
Author(s):  
Dominika Dudzińska ◽  
Adam Piórkowski
Keyword(s):  
Tissue Differentiation ◽  
Morphometric Features

Alzheimer's Disease Classification Based on Multi-feature Fusion

2019 ◽  
Vol 15 (2) ◽  
pp. 161-169 ◽  
Author(s):  
Nuwan Madusanka ◽  
Heung-Kook Choi ◽  
Jae-Hong So ◽  
Boo-Kyeong Choi
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Feature Fusion ◽  
Biological Data ◽  
Correct Classification ◽  
Mr Images ◽  
Correct Classification Rate ◽  
Classification Rate ◽  
Morphometric Features

Background: In this study, we investigated the fusion of texture and morphometric features as a possible diagnostic biomarker for Alzheimer’s Disease (AD). Methods: In particular, we classified subjects with Alzheimer’s disease, Mild Cognitive Impairment (MCI) and Normal Control (NC) based on texture and morphometric features. Currently, neuropsychiatric categorization provides the ground truth for AD and MCI diagnosis. This can then be supported by biological data such as the results of imaging studies. Cerebral atrophy has been shown to correlate strongly with cognitive symptoms. Hence, Magnetic Resonance (MR) images of the brain are important resources for AD diagnosis. In the proposed method, we used three different types of features identified from structural MR images: Gabor, hippocampus morphometric, and Two Dimensional (2D) and Three Dimensional (3D) Gray Level Co-occurrence Matrix (GLCM). The experimental results, obtained using a 5-fold cross-validated Support Vector Machine (SVM) with 2DGLCM and 3DGLCM multi-feature fusion approaches, indicate that we achieved 81.05% ±1.34, 86.61% ±1.25 correct classification rate with 95% Confidence Interval (CI) falls between (80.75-81.35) and (86.33-86.89) respectively, 83.33%±2.15, 84.21%±1.42 sensitivity and 80.95%±1.52, 85.00%±1.24 specificity in our classification of AD against NC subjects, thus outperforming recent works found in the literature. For the classification of MCI against AD, the SVM achieved a 76.31% ± 2.18, 78.95% ±2.26 correct classification rate, 75.00% ±1.34, 76.19%±1.84 sensitivity and 77.78% ±1.14, 82.35% ±1.34 specificity. Results and Conclusion: The results of the third experiment, with MCI against NC, also showed that the multiclass SVM provided highly accurate classification results. These findings suggest that this approach is efficient and may be a promising strategy for obtaining better AD, MCI and NC classification performance.

scholarly journals Classification of otoliths of fishes common in the Santa Barbara Basin based on morphology and chemical composition

2017 ◽  
Vol 74 (8) ◽  
pp. 1195-1207 ◽  
Author(s):  
William A. Jones ◽  
David M. Checkley
Keyword(s):  
Chemical Composition ◽  
Cross Validation ◽  
Function Analysis ◽  
Demersal Fish ◽  
Santa Barbara ◽  
Santa Barbara Basin ◽  
Multiple Feature ◽  
Morphometric Features ◽  
Taxonomic Groups

Morphological and chemical features of fish otoliths are used to distinguish between populations and stocks. We hypothesized that these features can also be used to distinguish between fishes of different taxonomic groups common in and near the Santa Barbara Basin, including mesopelagic, pelagic, and demersal fish. Sagittal otoliths obtained from 905 fish representing six taxonomic groups were imaged, and 12 geometric and 59 elliptic Fourier morphometric features were extracted. A subset of 143 otoliths was also analyzed for Li, Na, Mg, K, Mn, Sr, and Ba. We used chemical composition in addition to morphology because the latter may be altered between otolith formation and analysis. Two sets of classifiers were made: one using only morphometric features and one using both morphometric and element features. Random forest analysis was generally superior to discriminant function analysis. Highest classification success, evaluated using cross-validation and otoliths of masked identity, was achieved with multiple feature types. The ten strongest discriminatory features of all available feature types were used in the final classification models. Our method is applicable to the classification of otoliths recovered from guts, feces, middens, and sediments as well to classify other biological objects.

scholarly journals Clinical significance of variant anatomy of the celiac trunk

2018 ◽  
Vol 20 (1) ◽  
pp. 235-239
Author(s):  
I V Gaivoronsky ◽  
B N Kotiv ◽  
N A Kovalenko ◽  
Yu V Pelipas ◽  
Sh B Bahovadinova ◽  
...  
Keyword(s):  
Clinical Significance ◽  
Abdominal Aorta ◽  
Significant Risk ◽  
Celiac Trunk ◽  
Comparative Aspect ◽  
Morphometric Features ◽  
Lethal Complications ◽  
Characteristics Development ◽  
Variant Anatomy

Data on variant anatomy of the celiac trunk, typical and atypical variants of its architectonics, topography, existing classifications, morphometric characteristics, development of the vessels of abdominal aorta in embryogenesis and the clinical significance of anatomical features is presented. The issues under consideration are important for surgical practice, in particular, for abdominal surgery, transplantology, interventional X-ray endovascular surgery and oncosurgery. It is shown that the anatomy of the celiac trunk and its branches have a pronounced variability, and more than 15% of the population have significant deviations from the typical branching variant. A significant number of different variants of the celiac trunk dividing, a different frequency of occurrence of these variants, morphometric indices, apparently depends on the size of the sample of the investigated objects, gender and other reasons. Data on the development of branches of the abdominal aorta in embryogenesis and the causes of atypical variants is presented. In a comparative aspect, existing classifications of the most authoritative authors are considered. It is shown that, despite the large number, there is no universal, simplest in practice, classification of variants of the celiac trunk branching. Nosological examples that demonstrate the need to take into account the variant of formation of the celiac trunk and its morphometric features in operative and diagnostic manipulations on the organs and vessels of the upper floor of the peritoneal cavity are analyzed. Certainly without understanding the architectonics of the gastrosplenicpancreatoduodenal zone arteries, there is a significant risk of error, which can even lead to lethal complications.

Artificial Intelligence via Competitive Learning and Image Analysis for Endometrial Malignancies

2019 ◽  
Vol 8 (4) ◽  
pp. 38-54 ◽  
Author(s):  
Abraham Pouliakis ◽  
Niki Margari ◽  
Effrosyni Karakitsou ◽  
George Valasoulis ◽  
Nektarios Koufopoulos ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Image Analysis ◽  
System Performance ◽  
Malignant Disease ◽  
Competitive Learning ◽  
Image Analysis System ◽  
Morphometric Features ◽  
Analysis System ◽  
Histological Confirmation

Objective of this study is to investigate the potential of an artificial intelligence (AI) technique, based on competitive learning, for the discrimination of benign from malignant endometrial nuclei and lesions. For this purpose, 416 liquid-based cytological smears with histological confirmation were collected, each smear corresponded to one patient. From each smear was extracted nuclear morphometric features by the application of an image analysis system. Subsequently nuclei measurement from 50% of the cases were used to train the AI system to classify each individual nucleus as benign or malignant. The remaining measurement, from the unused 50% of the cases, were used for AI system performance evaluation. Based on the results of nucleus classification the patients were discriminated as having benign or malignant disease by a secondary subsystem specifically trained for this purpose. Based on the results it was conclude that AI based computerized systems have the potential for the classification of both endometrial nuclei and lesions.

scholarly journals Multiscale Landforms Classification Based on UAV Datasets

2018 ◽  
Vol 3 (2) ◽  
pp. 128
Author(s):  
Jean A. Doumit
Keyword(s):  
Unmanned Aerial Vehicles ◽  
High Spatial Resolution ◽  
Topographic Position Index ◽  
Topographic Slope ◽  
Morphometric Features ◽  
Surface Models ◽  
Very High Spatial Resolution ◽  
Position Index ◽  
Very High

<p><em>The advance uses of Unmanned Aerial Vehicles (UAV) in geosciences by producing very high spatial resolution Digital Surface Models (DSMs), the various UAV flight altitudes led to different scales DSM. In this paper, we analyzed terrain forms using Topographic Position Index (TPI), landforms extracted by Iwahashi and Pike method and morphometric features</em><em> </em><em>of three different spatial resolutions DSM processed from different UAV flights height datasets of the same study area.</em></p><p><em>Topographic </em><em>P</em><em>osition </em><em>I</em><em>ndex (TPI) is an algorithm for measuring topographic slope positions and to automate landform classi?cations,</em><em> </em><em>Iwahashi and Pike had developed an unsupervised method for classification of Landforms and we have used the techniques developed by Peuker and Douglas, a method classifying terrain surfaces into 7 classes.</em><em></em></p><em><em>Landforms extracted from the three indices listed above at the three flight heights of 120, 240 and 360 meters and compared with each other to understand the generalization of different scale and to highlight which landforms are more affected by the scale changes.</em><br /></em>

Forensic evaluation of age by X-ray morphometric features of the arytenoid cartilage of the human laryngeal complex

2021 ◽  
Vol 22 (1) ◽  
pp. 20-25
Author(s):  
V. N. Zvyagin ◽  
◽  
O. I. Galitskaya ◽  
R. R. Kalimullin ◽  
◽  
...  
Keyword(s):  
Regression Models ◽  
Age Groups ◽  
Forensic Evaluation ◽  
Arytenoid Cartilage ◽  
X Ray ◽  
Human Corpse ◽  
Morphometric Features ◽  
Age Dependent

The aim of the study was to develop a method for age evaluation based on the mineralization signs of the larynx arytenoid cartilage (AC) during the destroyed human corpse expertise. X-ray images of isolated AC preparations from both sexes (male – 264, female – 106) aged from 19 to 91 years were studied. Morphometry was conducted on: the area (in mm2) and the degree (%) of mineralization of both AC separately and united, a total of 6 features. Results. There is no correlation between the signs of AC mineralization and the length of the human body (r = 0.01-0.201). The correlation of these signs with age is high in men, (r = 0.741-0.781), and moderate in women (r = 0.470-0.508). There is a pronounced correlation between all age-dependent signs of AC (r = 0.948-0.985). According to the discriminant analysis results, the correct classification of the age groups 19-44 and 45-91 years is 82.9% in men, 77.03% in women. Practically reliable and probable diagnostics of men age is possible in 32.58 and 33.33%, of women age – in 5.41 and 37.84% of cases. According to the regression analysis, the age diagnostics in the range from 19 to 91 years in men is possible with an accuracy of ± 10.02 years (R = 0.799; R2 = 0.635), in women – ± 18.864 years (R = 0.506; R2 = –0.249). Forensic determination of the women age by regression models is excluded.

Note on the spectral classification of carbon stars in the photographic infrared region

1966 ◽  
Vol 24 ◽  
pp. 21-23
Author(s):  
Y. Fujita
Keyword(s):  
Infrared Region ◽  
Spectral Classification ◽  
Carbon Stars

We have investigated the spectrograms (dispersion: 8Å/mm) in the photographic infrared region fromλ7500 toλ9000 of some carbon stars obtained by the coudé spectrograph of the 74-inch reflector attached to the Okayama Astrophysical Observatory. The names of the stars investigated are listed in Table 1.

Diagnostic Value of Electron Microscopy in Soft Tissue Tumors

1970 ◽  
Vol 28 ◽  
pp. 220-221
Author(s):  
Gerald Fine ◽  
Azorides R. Morales
Keyword(s):  
Cardiac Myxoma ◽  
Osteogenic Sarcoma ◽  
Diagnostic Value ◽  
Soft Tissue Tumors ◽  
Amelanotic Melanoma ◽  
Growth Patterns ◽  
Light Microscopic Level ◽  
Mesenchymal Tumors ◽  
Good Agreement

For years the separation of carcinoma and sarcoma and the subclassification of sarcomas has been based on the appearance of the tumor cells and their microscopic growth pattern and information derived from certain histochemical and special stains. Although this method of study has produced good agreement among pathologists in the separation of carcinoma from sarcoma, it has given less uniform results in the subclassification of sarcomas. There remain examples of neoplasms of different histogenesis, the classification of which is questionable because of similar cytologic and growth patterns at the light microscopic level; i.e. amelanotic melanoma versus carcinoma and occasionally sarcoma, sarcomas with an epithelial pattern of growth simulating carcinoma, histologically similar mesenchymal tumors of different histogenesis (histiocytoma versus rhabdomyosarcoma, lytic osteogenic sarcoma versus rhabdomyosarcoma), and myxomatous mesenchymal tumors of diverse histogenesis (myxoid rhabdo and liposarcomas, cardiac myxoma, myxoid neurofibroma, etc.)

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