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A supervised approach to musculoskeletal imaging fracture detection and classification using deep learning algorithms

Karanam Santoshachandra Rao, Srinivas Y., Chakravarty S.

Computer Assisted Methods in Engineering and Science

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2023

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Vol. 30, no. 3

369--385

EN

Bone fractures break bone continuity. Impact or stress causes numerous bone fractures. Fracture misdiagnosis is the most frequent mistake in emergency rooms, resulting in treatment delays and permanent impairment. According to the Indian population studies, fractures are becoming more common. In the last three decades, there has been a growth of 480 000, and by 2022, it will surpass 600 000. Classifying X-rays may be challenging, particularly in an emergency room when one must act quickly. Deep learning techniques have recently become more popular for image categorization. Deep neural networks (DNNs) can classify images and solve challenging problems. This research aims to build and evaluate a deep learning system for fracture identification and bone fracture classification (BFC). This work proposes an image-processing system that can identify bone fractures using X-rays. Images from the dataset are pre-processed, enhanced, and extracted. Then, DNN classifiers ResNeXt101, InceptionResNetV2, Xception, and NASNetLarge separate the images into the ones with unfractured and fractured bones (normal, oblique, spiral, comminuted, impacted, transverse, and greenstick). The most accurate model is InceptionResNetV2, with an accuracy of 94.58%.

2

Filtracja zdjęć lotniczych w celu podwyższenia dokładności automatycznej aerotriangulacji cyfrowej

Kędzierski M.

Archiwum Fotogrametrii, Kartografii i Teledetekcji

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2004

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Vol. 14

1--12

PL

W referacie zostanie omówiona możliwość wykorzystania filtracji skanowanych zdjęć lotniczych i sposoby odpowiedniego wzmocnienia obrazu w celu podwyższenia dokładności automatycznej aerotriangulacji cyfrowej. Obecnie w Polsce i na świecie zdjęcia używane do aerotriangulacji nie są poddawane filtracji. W praktyce takie podejście z uwagi na niejednorodność materiału i różnice w jakości poszczególnych zdjęć od razu narzuca wyższe błędy aerotriangulacji cyfrowej. W referacie został zaprezentowany autorski sposób odpowiedniego wzmocnienia obrazu dający wzrost dokładności automatycznej aerotriangulacji cyfrowej.

3

On the segmentation of the Comet Assay images

Smolka B., Szczepański M., Świerniak A., Palus H., Plataniotis K. N.

Journal of Medical Informatics & Technologies

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2001

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Vol. 2, Part. 1

MI29--MI39

EN

The single cell gel electrophoresis, called Comet Assay is a microelectrophoretic technique of direct visualization of DNA damage at the cell level. In the comet assay, the cells suspended in an agarose gel on a microscope slide are subjected to lysis, unwinding of DNA and electrophoresis. After staining with fluorescent DNA binding dye, cells with DNA damage display increased migration of genetic material from the cell nucleus. Under the influence of weak, statics electric field, charged DNA migrates away from the nucleus forming a so called comet. The damage is quantified by measuring the amound of the genetic material, which migrates from the nucleus to form the comet tail. The foremost advantage of the comet assay is that it analyses individual cells, thus allowing the measurement of the heterogeneity of response within a cell population. In this paper we present three novel method of the comet tail and head extraction.

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On the noise attenuation in DNA microarray images

Smolka B., Szczepański M., Wojciechowski K., Plataniotis K. N.

Journal of Medical Informatics & Technologies

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2001

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Vol. 2, Part. 1

MI19--MI27

EN

In this paper a novel method of noise reduction in color images is presented. The new technique is capable of attenuating both impulsive and Gaussian noise, while preserving and even enhancing sharpness of the image edges. Extensive simulations reveal that the new method outperforms significantly the standard techniques widely used in multivariate signal processing. In this work we apply the new noise reduction method for the enhancement of the images of gene chips. We demonstrate that the new technique is capable of reducing various kinds of noise present in microarray images and that it enables efficient spot location and estimation of the gene expression level due to the smoothing effect and preservation of the spot edges. This paper contains the comparison of the new technique of noise reduction with the standard procedures used for the processing of vector valued images, as well as examples of the efficiency of the new algorithm when applied to typical microarray images.