Real-time prediction of quality characteristics in laser beam welding using optical coherence tomography and machine learning

2020 ◽  
Vol 32 (2) ◽  
pp. 022046
Author(s):  
Christian Stadter ◽  
Maximilian Schmoeller ◽  
Lara von Rhein ◽  
Michael F. Zaeh
Keyword(s):  
Machine Learning ◽  
Optical Coherence Tomography ◽  
Laser Beam ◽  
Real Time ◽  
Laser Beam Welding ◽  
Quality Characteristics ◽  
Optical Coherence ◽  
Time Prediction

Process control and quality assurance in remote laser beam welding by optical coherence tomography

2019 ◽  
Vol 31 (2) ◽  
pp. 022408
Author(s):  
Christian Stadter ◽  
Maximilian Schmoeller ◽  
Martin Zeitler ◽  
Volkan Tueretkan ◽  
Ulrich Munzert ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Quality Assurance ◽  
Process Control ◽  
Laser Beam ◽  
Laser Beam Welding ◽  
Optical Coherence

scholarly journals Unraveling the deep learning gearbox in optical coherence tomography image segmentation towards explainable artificial intelligence

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Peter M. Maloca ◽  
Philipp L. Müller ◽  
Aaron Y. Lee ◽  
Adnan Tufail ◽  
Konstantinos Balaskas ◽  
...  
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Optical Coherence Tomography ◽  
Image Segmentation ◽  
Convolutional Neural Network ◽  
Learning Algorithm ◽  
Ground Truth ◽  
Optical Coherence Tomography Image ◽  
Optical Coherence ◽  
Tomography Image

AbstractMachine learning has greatly facilitated the analysis of medical data, while the internal operations usually remain intransparent. To better comprehend these opaque procedures, a convolutional neural network for optical coherence tomography image segmentation was enhanced with a Traceable Relevance Explainability (T-REX) technique. The proposed application was based on three components: ground truth generation by multiple graders, calculation of Hamming distances among graders and the machine learning algorithm, as well as a smart data visualization (‘neural recording’). An overall average variability of 1.75% between the human graders and the algorithm was found, slightly minor to 2.02% among human graders. The ambiguity in ground truth had noteworthy impact on machine learning results, which could be visualized. The convolutional neural network balanced between graders and allowed for modifiable predictions dependent on the compartment. Using the proposed T-REX setup, machine learning processes could be rendered more transparent and understandable, possibly leading to optimized applications.

scholarly journals Multi-center clinical study using optical coherence tomography for evaluation of cervical lesions in-vivo

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chenchen Ren ◽  
Xianxu Zeng ◽  
Zhongna Shi ◽  
Chunyan Wang ◽  
Huifen Wang ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Real Time ◽  
Precancerous Lesions ◽  
Diagnostic Value ◽  
Optical Coherence ◽  
Cervical Lesions ◽  
In Vivo Evaluation ◽  
Histological Sections ◽  
Histological Images

AbstractIn this prospective study of an in-vivo cervical examination using optical coherence tomography (OCT), we evaluated the diagnostic value of non-invasive and real-time OCT in cervical precancerous lesions and cancer diagnosis, and determined the characteristics of OCT images. 733 patients from 5 Chinese hospitals were inspected with OCT and colposcopy-directed biopsy. The OCT images were compared with the histological sections to find out the characteristics of various categories of lesions. The OCT images were also interpreted by 3 investigators to make a 2-class classification, and the results were compared against the pathological results. Various structures of the cervical tissue were clearly observed in OCT images, which matched well with the corresponding histological sections. The OCT diagnosis results delivered a sensitivity of 87.0% (95% confidence interval, CI 82.2–90.7%), a specificity of 84.1% (95% CI 80.3–87.2%), and an overall accuracy of 85.1%. Both good consistency of OCT images and histological images and satisfactory diagnosis results were provided by OCT. Due to its features of non-invasion, real-time, and accuracy, OCT is valuable for the in-vivo evaluation of cervical lesions and has the potential to be one of the routine cervical diagnosis methods.

scholarly journals Real-time speckle variance swept-source optical coherence tomography using a graphics processing unit

2012 ◽  
Vol 3 (7) ◽  
pp. 1557 ◽  
Author(s):  
Kenneth K. C. Lee ◽  
Adrian Mariampillai ◽  
Joe X. Z. Yu ◽  
David W. Cadotte ◽  
Brian C. Wilson ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Real Time ◽  
Graphics Processing Unit ◽  
Processing Unit ◽  
Optical Coherence ◽  
Swept Source ◽  
Graphics Processing
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