Conversion of Laser Ultrasonic Tomography Data to the DICOM Standard

Electrical capacitance tomography (ECT) is one of process tomography technique which is developed rapidly in recent years. ECT is an imaging technique to obtain the internal permittivity distribution of a vessel or pipe by using capacitance electrodes sensor. This method has been integrated with ultrasonic tomography as multimodality system to perform multiphase flow measurement such as crude oil separation and oil process industry. In the present paper, a novel type of ECT sensor was developed using copper FR4 material. The electrode sensors can be flexibly bend or curve to fit the pipe surface for optimum measurement. Thus, every single sensor strip is designed to be functioned independently. Such system has lower sensing capability in the central of the sensing area which often contributes to poor imaging result. This problem can be overcome by combining the ECT with ultrasonic tomography to form a dual modality tomography system. By implementing the new ECT sensor, multiphase flow measurement image results can be achieved. The reconstructed image results are presented in this paper.

Download Full-text

Parasitic capacitances estimation of an Electrical Impedance Tomography data acquisition system by Bayesian inference

Measurement ◽

10.1016/j.measurement.2021.108992 ◽

2021 ◽

Vol 174 ◽

pp. 108992

Author(s):

Adriana Machado Malafaia da Mata ◽

Bruno Furtado de Moura ◽

Marcio Ferreira Martins ◽

Francisco Hernán Sepúlveda Palma ◽

Rogério Ramos

Keyword(s):

Bayesian Inference ◽

Data Acquisition ◽

Electrical Impedance Tomography ◽

Electrical Impedance ◽

Data Acquisition System ◽

Acquisition System ◽

Impedance Tomography ◽

Tomography Data ◽

Electrical Impedance Tomography Data

Download Full-text

Automatic Quantification Of Subsurface Defects By Analyzing Laser Ultrasonic Signals Using Convolutional Neural Networks And Wavelet Transform

IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control ◽

10.1109/tuffc.2021.3087949 ◽

2021 ◽

pp. 1-1

Author(s):

Shifeng Guo ◽

Haowen Feng ◽

Wei Fenga ◽

Gaolong Lv ◽

Dan Chen ◽

...

Keyword(s):

Neural Networks ◽

Wavelet Transform ◽

Convolutional Neural Networks ◽

Laser Ultrasonic ◽

Automatic Quantification ◽

Ultrasonic Signals ◽

Subsurface Defects

Download Full-text

Characterization of Precipitation in 7055 Aluminum Alloy by Laser Ultrasonics

Metals ◽

10.3390/met11020275 ◽

2021 ◽

Vol 11 (2) ◽

pp. 275

Author(s):

Zhenge Zhu ◽

Hao Peng ◽

Yacheng Xu ◽

Xueyong Song ◽

Jinrong Zuo ◽

...

Keyword(s):

Aluminum Alloy ◽

Electron Microscope ◽

Laser Ultrasonics ◽

Precipitate Size ◽

Destructive Testing ◽

Laser Ultrasonic ◽

Precipitated Phase ◽

Transmission Electron ◽

7055 Aluminum Alloy ◽

The Time Domain

After different rolling conditions, four 7055 aluminum alloy samples with different precipitation sizes were measured by scanning electron microscope, transmission electron microscope and laser ultrasonic. The attenuation coefficients of ultrasound measured by laser ultrasonic were calculated in the time domain, frequency domain and wavelet denoising, respectively. The relationship between the precipitate size and attenuation coefficient was established. The results show that the attenuation of the ultrasonic wave is related to the size of the precipitated phase; this provides a new method for rapid non-destructive testing of the precipitation of aluminum alloys.

Download Full-text

A DICOM dataset for evaluation of medical image de-identification

Scientific Data ◽

10.1038/s41597-021-00967-y ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Michael Rutherford ◽

Seong K. Mun ◽

Betty Levine ◽

William Bennett ◽

Kirk Smith ◽

...

Keyword(s):

Health Information ◽

National Cancer Institute ◽

Medical Image ◽

Cancer Imaging ◽

Protected Health Information ◽

Dicom Standard ◽

Clinical Imaging ◽

X Ray ◽

Evaluation Dataset ◽

Data Elements

AbstractWe developed a DICOM dataset that can be used to evaluate the performance of de-identification algorithms. DICOM objects (a total of 1,693 CT, MRI, PET, and digital X-ray images) were selected from datasets published in the Cancer Imaging Archive (TCIA). Synthetic Protected Health Information (PHI) was generated and inserted into selected DICOM Attributes to mimic typical clinical imaging exams. The DICOM Standard and TCIA curation audit logs guided the insertion of synthetic PHI into standard and non-standard DICOM data elements. A TCIA curation team tested the utility of the evaluation dataset. With this publication, the evaluation dataset (containing synthetic PHI) and de-identified evaluation dataset (the result of TCIA curation) are released on TCIA in advance of a competition, sponsored by the National Cancer Institute (NCI), for algorithmic de-identification of medical image datasets. The competition will use a much larger evaluation dataset constructed in the same manner. This paper describes the creation of the evaluation datasets and guidelines for their use.

Download Full-text