Journal of X-Ray Science and Technology 
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This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.A hybrid thyroid tumor type classification system using feature fusion, multilayer perceptron and bonobo optimization
CONCLUSION: It can be observed from the results that the proposed multilayer perceptron based thyroid tumor type classification system works in an efficient manner than the existing classifiers like CANFES, Spatial Fuzzy C means, Deep Belief Networks, Thynet and Generative adversarial network and Long Short-Term memory.PMID:38393884 | DOI:10.3233/XST-230430 (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - February 23, 2024 Category: Radiology Authors: B Shankarlal S Dhivya K Rajesh S Ashok Source Type: research
Lossless compression-based detection of osteoporosis using bone X-ray imaging
CONCLUSIONS: The proposed method effectively distinguishes between osteoporotic and non-osteoporotic cases using bone X-ray images. By enhancing image features and employing SVM classification, the technique offers a promising tool for efficient and accurate osteoporosis diagnosis.PMID:38393881 | DOI:10.3233/XST-230238 (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - February 23, 2024 Category: Radiology Authors: Khalaf Alshamrani Hassan A Alshamrani Source Type: research
Machine learning framework for simulation of artifacts in paranasal sinuses diagnosis using CT images
In this study, a unique method is presented for detecting and diagnosing paranasal sinus disorders using machine learning. The researchers behind the current study designed their own approach. To speed up diagnosis, one of the primary goals of our study is to create an algorithm that can accurately evaluate the paranasal sinuses in CT scans. The proposed technology makes it feasible to automatically cut down on the number of CT scan images that require investigators to manually search through them all. In addition, the approach offers an automatic segmentation that may be used to locate the paranasal sinus region and crop ...
Source: Journal of X-Ray Science and Technology - February 23, 2024 Category: Radiology Authors: Abdullah Musleh Source Type: research
Performance evaluation of deep learning image reconstruction algorithm for dual-energy spectral CT imaging: A phantom study
CONCLUSIONS: DLIR provides better noise containment for low keV images in DEsCT and higher TTF(50%) for the polystyrene insert over ASIR-V. DLIR-H has the lowest image noise and highest detectability in all dose and energy levels. DEsCT 50 keV images with DLIR-M and DLIR-H show potential for 65% dose reduction over ASIR-V50% withhigher d'.PMID:38393883 | DOI:10.3233/XST-230333 (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - February 23, 2024 Category: Radiology Authors: Haoyan Li Zhentao Li Shuaiyi Gao Jiaqi Hu Zhihao Yang Yun Peng Jihang Sun Source Type: research
A hybrid thyroid tumor type classification system using feature fusion, multilayer perceptron and bonobo optimization
CONCLUSION: It can be observed from the results that the proposed multilayer perceptron based thyroid tumor type classification system works in an efficient manner than the existing classifiers like CANFES, Spatial Fuzzy C means, Deep Belief Networks, Thynet and Generative adversarial network and Long Short-Term memory.PMID:38393884 | DOI:10.3233/XST-230430 (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - February 23, 2024 Category: Radiology Authors: B Shankarlal S Dhivya K Rajesh S Ashok Source Type: research
Lossless compression-based detection of osteoporosis using bone X-ray imaging
CONCLUSIONS: The proposed method effectively distinguishes between osteoporotic and non-osteoporotic cases using bone X-ray images. By enhancing image features and employing SVM classification, the technique offers a promising tool for efficient and accurate osteoporosis diagnosis.PMID:38393881 | DOI:10.3233/XST-230238 (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - February 23, 2024 Category: Radiology Authors: Khalaf Alshamrani Hassan A Alshamrani Source Type: research
Machine learning framework for simulation of artifacts in paranasal sinuses diagnosis using CT images
In this study, a unique method is presented for detecting and diagnosing paranasal sinus disorders using machine learning. The researchers behind the current study designed their own approach. To speed up diagnosis, one of the primary goals of our study is to create an algorithm that can accurately evaluate the paranasal sinuses in CT scans. The proposed technology makes it feasible to automatically cut down on the number of CT scan images that require investigators to manually search through them all. In addition, the approach offers an automatic segmentation that may be used to locate the paranasal sinus region and crop ...
Source: Journal of X-Ray Science and Technology - February 23, 2024 Category: Radiology Authors: Abdullah Musleh Source Type: research
Performance evaluation of deep learning image reconstruction algorithm for dual-energy spectral CT imaging: A phantom study
CONCLUSIONS: DLIR provides better noise containment for low keV images in DEsCT and higher TTF(50%) for the polystyrene insert over ASIR-V. DLIR-H has the lowest image noise and highest detectability in all dose and energy levels. DEsCT 50 keV images with DLIR-M and DLIR-H show potential for 65% dose reduction over ASIR-V50% withhigher d'.PMID:38393883 | DOI:10.3233/XST-230333 (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - February 23, 2024 Category: Radiology Authors: Haoyan Li Zhentao Li Shuaiyi Gao Jiaqi Hu Zhihao Yang Yun Peng Jihang Sun Source Type: research
A hybrid thyroid tumor type classification system using feature fusion, multilayer perceptron and bonobo optimization
CONCLUSION: It can be observed from the results that the proposed multilayer perceptron based thyroid tumor type classification system works in an efficient manner than the existing classifiers like CANFES, Spatial Fuzzy C means, Deep Belief Networks, Thynet and Generative adversarial network and Long Short-Term memory.PMID:38393884 | DOI:10.3233/XST-230430 (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - February 23, 2024 Category: Radiology Authors: B Shankarlal S Dhivya K Rajesh S Ashok Source Type: research
Special Section: Medical Applications of X-ray Imaging Techniques
J Xray Sci Technol. 2024;32(1):105.NO ABSTRACTPMID:38339917 (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - February 10, 2024 Category: Radiology Source Type: research
