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Classifying median nerves in carpal tunnel syndrome: Ultrasound image analysis

Obuchowicz Rafał, Kruszyńska Julia, Strzelecki Michał

Biocybernetics and Biomedical Engineering

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2021

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Vol. 41, no. 2

335--351

EN

Rationale and objectives: Carpal tunnel syndrome (CTS) refers to a common median nerve pathology, which is related to an increased pressure in the fibrous/bone canal of the wrist. Ultrasound gained popularity recently as a useful tool for the accurate and repetitive diagnosis of carpal tunnel syndrome. The present study aimed to develop an objective, repetitive technique for assessing median nerves based on carpal tunnel ultrasound texture analysis. Material and methods: Sixty ultrasound images, including 30 images of swollen ‘‘symptomatic” median nerves and 30 normal ‘‘asymptomatic” median nerves, were used in this study. Narrow age group of patients were selected. They were recruited after positive nerve conduction study and with present clinical symptoms reviled on basis of interview and written questionnaire. Meticulous nerve area and echogenicity assessment were conducted in line with existing recommendations. Results: Using the feature-selection tool MaZda, an exhaustive search of the data space was conducted, and four texture features were found for which the classification was the most accurate. Images were classified using a support vector machine with a five-fold cross-verification in MATLAB. Evoked outcomes showed a 79% correct classification rate. Conclusion: Computer analysis of the image echogenicity of the median nerve presented confidence levels comparable to trusted evaluation techniques. Further, it is a promising tool for assessing the nerve’s status in CTS as approach of the CTS assessment free from subjectivity of examiner. The developed method enables nerve classification based on echogenicity that reflects the nerve composition changes not only subjective nerve area assessment.

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Automatic seed point selection in ultrasound echography images of breast using texture features

Selvan S., Shenbaga Devi S.

Biocybernetics and Biomedical Engineering

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2015

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Vol. 35, no. 3

157--168

EN

Automatic segmentation of breast lesions in 2D ultrasound B-scan images via active contours, require a seed point to be selected inside the breast lesion. The grey levels on an ultrasound image of the breast show intensity information. The fat tissue is hypo echoic relative to the surrounding glandular tissue. The glandular parenchyma tissue usually appears homogeneously echogenic as compared with fat lobules. Simple cysts are anechoic. Malignant solid masses are usually heterogeneous, hypo echoic and tend to look intensely black compared to surrounding isoechoic fat. Benign solid masses tend to appear on ultrasound with intense and uniform hyper echogenicity. Texture features represent changes in grey level intensities. This paper proposes a method that can automatically identify a seed point based on texture features and allow automatic contour initialization for level set segmentation. This seed point plotted on an US B-scan image is mapped on to its corresponding elastogram pair. The proposed approach is applied to 199 ultrasound B-scan images of which 52 are benign solid masses, 84 malignant solid masses and 63 simple and complex cysts. The seed point obtained using this approach is mapped to its corresponding elastogram pair in 62 US B-scan and US elastography image pairs. Quantitative experiment results show that our proposed approach can successfully find proper seed points based on texture values, in ultrasound B-scan images and therefore in elastography images, with an overall accuracy of 86.93%. This approach is effective and makes segmentation of breast lesions computationally easier, more accurate and fast.

3

Parametry stosowane do oceny obrazów ultrasonograficznych wysokich częstotliwości skóry

Wawrzyniak Z. M., Malinowska S., Mlosek R.K.

Inżynier i Fizyk Medyczny

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2013

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Vol. 2, nr 4

222--226

PL

Badania ultrasonograficzne wysokich częstotliwości skóry wykonywane są za pomocą klasycznych ultrasonografów, wyposażonych w głowice o częstotliwościach powyżej 20 MHz lub aparatów wysokich częstotliwości dedykowanych do tego celu. Stosowane do badań aparaty pozwalają obrazować skórę w wysokiej rozdzielczości i oceniać struktury o wielkości lub grubości mniejszej niż 0,1 mm. Ultrasonograficzne obrazowanie skóry wykorzystywane jest głównie do monitorowania przebiegu leczenia chorób skóry, tj. twardziny, łuszczycy oraz do oceny zmian ogniskowych. Ultrasonografia skóry znalazła również zastosowanie w medycynie estetycznej i kosmetologii, gdzie służy do oceny stanu skóry oraz monitorowania prowadzonych terapii. Obecnie ultrasonograficzne obrazy skóry ocenianie są w oparciu o analizę jakościową (ocena wizualna) oraz analizę ilościową – pomiary grubości poszczególnych struktur, pola powierzchni oraz echogeniczności. W analizie obrazów USG szczególnie użytecznym parametrem jest echogeniczność i wynikająca z niej ocena obrazu. Sposób wyznaczania i interpretowania tego parametru w przypadku badań skóry nie został jednak dotychczas szczegółowo opisany, dlatego też istotne jest prowadzenie prac badawczych mających na celu opracowanie parametrów do oceny skóry na obrazach ultrasonograficznych.

EN

Skin ultrasound scans are taken using conventional ultrasound devices, equipped with > 20 MHz probes or high frequency (HF) ultrasound devices intended for skin testing. The ultrasound scanning devices allow for high resolution skin imaging and assessment of structures smaller/thinner than 0,1 mm. Ultrasound skin imaging is used in dermatology for treatment monitoring in patients with scleroderma, psoriasis or for the assessment of focal lesions. It has also proved to be useful in aesthetic medicine and cosmetology, for skin assessment and treatment monitoring. Currently, skin ultrasound scans are subjected both to qualitative (i.e. visual assessment) and quantitative (i.e. thickness of individual structures, areas and echogeneity measurements) analyses. The echogeneity parameter is particularly useful in ultrasound image assessment. However, the methodology for determining and interpreting this parameter in skin ultrasound scanning has not been described yet, therefore it is crucial to conduct further studies aiming at developing parameters of ultrasound skin assessment.