The field to be reconstructed was simulated with numerical simulation technique. The effect of a three-dimensional field's characteristics, especially, its frequency components, on the reconstructive accuracy was discussed with spectroscopy. A double-peaked field model was built with Gaussian function, and its frequency components were analyzed by Fourier transform. With algebraic reconstruction technique, the model field was reconstructed. The reconstructed field was analyzed with many error indexes. As a result, the reconstructed field was similar to the model one in respect of the position, pointing and shape of the peaks, but the heights of the peaks were shorter than those of corresponding ones in the model. The border of the reconstructive field showed obvious fluctuation. It was considered that the main causation of the reconstructive result was the filtering inserted in iterating process. To confirm this idea, the convergence factor, represented with A, of Gaussian function was changed from six to thirty in order to change the frequency components of the model field, and the same numerical simulation as the one for the first model field with A=18 was carried out for these new model ones consisting of different frequency. As a result, the idea proved to be right. At the same time, it was found that the characteristics of the field at the edge of the reconstructed zone had a deeper effect on the reconstructive accuracy. When the precondition that the field edge approximated to zero could no longer existed, the reconstructive accuracy declined, and furthermore, it would make iterating process divergent. From all the above, the characteristics of the field at the edge should draw much attention when we reconstruct a field with Algebraic reconstruction technique.
Download full-text PDF |
Source |
---|
Med Phys
January 2025
Deparment of Radiation Oncology, Duke University, Durham, North Carolina, USA.
Background: Stereotactic radiosurgery (SRS) is widely used for managing brain metastases (BMs), but an adverse effect, radionecrosis, complicates post-SRS management. Differentiating radionecrosis from tumor recurrence non-invasively remains a major clinical challenge, as conventional imaging techniques often necessitate surgical biopsy for accurate diagnosis. Machine learning and deep learning models have shown potential in distinguishing radionecrosis from tumor recurrence.
View Article and Find Full Text PDFJ Acoust Soc Am
January 2025
Urban Construction Center of Lucheng District of Wenzhou, Wenzhou, 325000, China.
The identification of vibration and reconstruction of sound fields of plate structures are important for understanding the vibroacoustic characteristics of complex structures. This paper presents a data-physics driven (DPD) model integrated with transfer learning (DPDT) for high-precision identification and reconstruction of vibration and noise radiation of plate structures. The model combines the Kirchhoff-Helmholtz integral equation with convolutional neural networks, leveraging physical information to reduce the need for extensive data.
View Article and Find Full Text PDFAntigen processing and presentation via major histocompatibility complex (MHC) molecules are central to immune surveillance. Yet, quantifying the dynamic activity of MHC class I and II antigen presentation remains a critical challenge, particularly in diseases like cancer, infection and autoimmunity where these pathways are often disrupted. Current methods fall short in providing precise, sample-specific insights into antigen presentation, limiting our understanding of immune evasion and therapeutic responses.
View Article and Find Full Text PDFScientific-grade spectrometers with high hyperspectral resolution and high spectral accuracy are desirable in miniaturized optical systems to maintain stable and real-time spectral sampling. Fourier transform spectrometers that utilize high-precision moving mirrors generally struggle to enhance their miniaturization and stable real-time performance. A static infrared spectral measurement method is proposed that uses micro/nano-optical devices as the core of static interference and lightweight imaging.
View Article and Find Full Text PDFSynchrotron X-ray microtomography (S-µCT) is a highly valuable technique for investigating organ function and pathologies. However, its application is often limited by high radiation doses and the occurrence of ring artifacts. While S-µCT utilizing sparse-view projections can effectively decrease radiation doses, the reconstructed images frequently exhibit severe streaking artifacts, which are exacerbated by ring artifacts, ultimately compromising reconstruction accuracy, image quality, and resolution.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!