• Clinics in Shoulder and Elbow
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• v.26 no.4
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• pp.366-372
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• 2023

Background: There is minimal literature on the morphology of partial distal biceps tendon (DBT) tears. We sought to investigate tear morphology by retrospectively reviewing 3-Tesla magnetic resonance imaging (3T MRI) scans of elbows with partial DBT tears and to propose a basic classification system. Methods: 3T MRI scans of elbows with partial DBT tears were retrospectively reviewed by two experienced observers. Basic demographic data were collected. Tear morphology was recorded including type, presence of retraction (>5 mm), and presence of discrete long-head and short-head tendons at the DBT insertion. Results: For analysis, 44 3T MRI scans of 44 elbows with partial DBT tears were included. There were 9 isolated long-head tears (20%), 13 isolated short-head tears (30%), 2 complete long-head tears with a partial short-head tear (5%), 5 complete short-head tears with a partial long-head tear (11%), and 15 peel-off tears (34%). Retraction was seen in 5 or 44 partial tears (11%), and 13 of the 44 DBTs were bifid tendons at the insertion (30%). Conclusions: Partial DBT tears can be classified into five sub-types: long-head isolated tears, short-head isolated tears, complete long-head tears with partial short-head involvement, complete short-head tears with partial long-head involvement, and peel-off tears. Classification of tears may have implications for operative and non-operative management. Level of evidence: III.

• Genomics & Informatics
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• v.2 no.1
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• pp.19-29
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• 2004

Gene expression profiles may offer more information than morphology and provide an alternative to morphology- based tumor classification systems. Informative gene selection is finding gene subsets that are able to discriminate between tumor types, and may have clear biological interpretation. Gene selection is a fundamental issue in gene expression based tumor classification. In this report, techniques for selecting informative genes are illustrated and supervised shaving introduced as a gene selection method in the place of a clustering algorithm. The supervised shaving method showed good performance in gene selection and classification, even though it is a clustering algorithm. Almost selected genes are related to leukemia disease. The expression profiles of 3051 genes were analyzed in 27 acute lymphoblastic leukemia and 11 myeloid leukemia samples. Through these examples, the supervised shaving method has been shown to produce biologically significant genes of more than $94\%$ accuracy of classification. In this report, SVM has also been shown to be a practicable method for gene expression-based classification.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.69.1-69.1
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• 2011

While the Virgo Cluster Catalog (VCC) is well established catalog from deep photographic plate survey, with available survey data recently released (e.g., SDSS), it can be further updated concerning the membership and morphology of galaxies. While membership and morphology of galaxies included in the VCC are based on the single band imaging data, thanks to the multi-color imaging and spectroscopic observations of SDSS, we are able to revise the membership and morphology of sample galaxies in the fields of the Virgo cluster. We present a new catalog of galaxies in the Virgo cluster using SDSS DR7 data, the extended Virgo cluster catalog. Using SDSS imaging and spectroscopic data, we introduce two kinds of galaxy classifications which are complementary each other. In addition to traditional morphological classification by visual inspection of the images ("Primary Classification"), we also attempt to classify galaxies with the spectroscopic features ("Secondary Classification"). The primary classification is basically based on the scheme of galaxy morphological classification of VCC. The secondary classification relies on the SED shape and presence of emission/absorption lines returned from SDSS. Our morphological classifications allow to study the evolution and associated star formation histories of galaxies in the Virgo cluster.

• Journal of Ecology and Environment
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• v.29 no.5
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• pp.425-432
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• 2006

The tadpoles of 12 Korean anuran species, including Bombina orientalis, Bufo gargarizans, B. stejnegeri, Hyla japonica, Kaloula borealis, Rana dybowskii, R. huanrenensis, R. coreana, R. nigromaculata, R. chosenica, R. rugosa, and R. catesbeiana, were classified based on their morphological characteristics. We collected eggs or tadpoles of the 12 Korean anuran species from Gangwon, Incheon, Chungcheong, and Gyeonggi districts in 2005 and 2006 breeding seasons. When the tadpoles reached at $27{\sim}37$ Gosner's developmental stages, we described morphological characteristics of the tadpoles of each anuran species and measured their physical parameters such as total length, body length, and body mass. After that, we chose 12 morphological characteristics to identify each species and to use them as classification keys such as eye location, caudal musculature pattern, spiracle location, oral disc morphology, and labial tooth row formula. In this paper, we presented classification keys, morphological characteristics, and drawings for the tadpoles of 12 anuran species.

• KSTLE International Journal
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• v.2 no.1
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• pp.35-39
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• 2001

In this paper, statistical approach is undertaken to investigate the classification of wear debris which is the key function of objective assessment of wear debris morphology. Wear tests are run to produce various kinds of wear debris. The images of wear debris from wear tests are captured with image acquisition equipment. By thresholding, two-dimensional binary images of wear debris are made and, then, morphological parameters are used to quantify the images of debris. Parametric and nonparametric discriminant method are employed to classify wear debris into predefined wear conditions. It is demonstrated that classification accuracy of parametric and nonparametric discriminant method is similar. The selected use of morphological parameters by stepwise discriminant analysis can generally improve the classification accuracy of parametric and nonparametric discriminant method.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.4
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• pp.22-30
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• 2001

In this paper we propose three classification algorithms to classify breast tumors that occur in duct into Benign, DCIS(ductal carcinoma in situ) NOS(invasive ductal carcinoma) The general approach for a creating classifier is composed of 2 steps: feature extraction and classification Above all feature extraction for a good classifier is very significance, because the classification performance depends on the extracted features, Therefore in the feature extraction step, we extracted morphology features describing the size of nuclei and texture features The internal structures of the tumor are reflected from wavelet transformed images with 10$\times$ and 40$\times$ magnification. Pariticulary to find the correlation between correct classification rates and wavelet depths we applied 1, 2, 3 and 4-level wavelet transforms to the images and extracted texture feature from the transformed images The morphology features used are area, perimeter, width of X axis width of Y axis and circularity The texture features used are entropy energy contrast and homogeneity. In the classification step, we created three classifiers from each of extracted features using discriminant analysis The first classifier was made by morphology features. The second and the third classifiers were made by texture features of wavelet transformed images with 10$\times$ and 40$\times$ magnification. Finally we analyzed and compared the correct classification rate of the three classifiers. In this study, we found that the best classifier was made by texture features of 3-level wavelet transformed images.

• Journal of Korean Dental Science
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• v.16 no.2
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• pp.156-163
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• 2023

Purpose: The aim of this study was to evaluate the feasibility of deep learning techniques to classify the morphology and severity of peri-implantitis bone defects based on periapical radiographs. Materials and Methods: Based on a pre-trained and fine-tuned ResNet-50 deep learning algorithm, the morphology and severity of peri-implantitis bone defects on periapical radiographs were classified into six groups (class I/II and slight/moderate/severe). Accuracy, precision, recall, and F1 scores were calculated to measure accuracy. Result: A total of 971 dental images were included in this study. Deep-learning-based classification achieved an accuracy of 86.0% with precision, recall, and F1 score values of 84.45%, 81.22%, and 82.80%, respectively. Class II and moderate groups had the highest F1 scores (92.23%), whereas class I and severe groups had the lowest F1 scores (69.33%). Conclusion: The artificial intelligence-based deep learning technique is promising for classifying the morphology and severity of peri-implantitis. However, further studies are required to validate their feasibility in clinical practice.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.387-388
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• 2010

There is no generalized and systematic method yet to data pre-processing for point cloud data classification even if there have been lots of previous studies such as local maxima filter, morphology filter, slope based filter and so on. Main focus of this study is to present classification method for bare ground information from LiDAR data for the mountainous area.

• Journal of Plant Biology
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• v.37 no.2
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• pp.245-252
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• 1994

Pollens of 20 species of Sedum were investigated with a scanning electron microscope. The pollen morphology of Sedum was rather variable, within particular species or even within a single inflorescence. Differences occurred in the number and shape of apertures and surface sculpture. Besides 3-colporate, various aperture types including 2-syncolporate, 3-syncolporate, 40stephanocolporate, 5-stephanocolporate, zonate, and irregular types were found in a single specimen. Also, striate-rugulose and psilate sculpture were found in S. viviparum. No correlation was found between the pollen morphology and the floral formula. Pollen characters appeared to be not useful for infrageneric classification of Korean Sedum.

• The korean journal of orthodontics
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• v.49 no.2
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• pp.81-88
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• 2019

Objective: The aim was to assess the intraobserver and interobserver reliabilities of temporomandibular joint linear measurements and condylar shape classifications performed with cone-beam computed tomography (CBCT). Methods: CBCT images of 30 patients were measured at two different time points by two orthodontists using the Dolphin 3D program (n = 60). Anterior, posterior, and superior joint space measurements and sagittal joint morphology classification in the sagittal view and medial and lateral joint space and mediolateral width measurements and coronal joint morphology classification in the coronal view were recorded. Intraclass-interclass correlation coefficients (ICC) and kappa statistics were used to assess intraobserver and interobserver reliability for the measurements and morphology classifications, respectively. Results: The ICC values were good for measurements of the posterior joint space by observer I and for measurements of the posterior, medial, and lateral joint spaces by observer II, while the other intraobserver measurements were excellent. Only the mediolateral width measurements showed excellent interobserver ICC values, while the other measurements showed good interobserver ICC values. Intraobserver agreement for the sagittal morphology classifications was moderate (${\kappa}=0.479$) and almost perfect (${\kappa}=0.858$) for observers I and II, respectively, while the corresponding agreement for the coronal morphology classifications was substantial for both observers. The interobserver agreement values for sagittal and coronal morphology classifications were slight (${\kappa}=0.181$) and fair (${\kappa}=0.265$), respectively. Conclusions: Linear temporomandibular joint measurements were reproducible and reliable in both intraobserver and interobserver evaluations. However, interobserver agreement for assessments of condylar shape was low.