Reduced iteration image reconstruction of incomplete projection CT using regularization strategy through Lp norm dictionary learning

Coronary Artery Magnetic Resonance Angiography Combined with Computed Tomography Angiography in Diagnosis of Coronary Heart Disease by Reconstruction Algorithm

This research aimed at discussing the diagnosis effect of coronary artery magnetic resonance angiography (MRA) combined with computed tomography (CT) angiography (CTA) based on the back-projection filter reconstruction (BPFR) algorithm in coronary heart disease (CHD), and its role in the diagnosis of coronary artery disease (CAD). Sixty patients with CHD were selected and randomly rolled into group A (undergone MRA examination), group B (undergone CTA examination), and group C (undergone MRA + CTA), with 20 cases in each group. Taking the diagnostic results of coronary angiography as the gold standard, the MRA and CTA images were reconstructed using a BPFR algorithm, and a filter function was added to solve the problem of image sharpness. In addition, the iterative reconstruction algorithm and the Fourier transform analysis method were introduced. As a result, the image clarity and resolution obtained by the BPFR algorithm were better than those obtained by the Fourier transform analytical method and the iterative reconstruction algorithm. The accuracy of group C for the diagnosis of mild coronary stenosis, moderate stenosis, and severe stenosis was 94.02%, 96.13%, and 98.01%, respectively, which was significantly higher than that of group B (87.5%, 90.2%, and 88.4%) and group C (83.4%, 89.1%, and 91.5%) (P < 0.05). The sensitivity and specificity for the diagnosis of noncalcified plaque in group C were 87.9% and 89.2%, respectively, and the sensitivity and specificity for the diagnosis of calcified plaque were 84.5% and 78.4%, respectively, which were significantly higher than those in groups B and C (P < 0.05). In summary, the BPFR algorithm had good denoising and artifact removal effects on coronary MRA and CTA images. The combined detection of reconstructed MRA and CTA images had a high diagnostic value for CHD.

Ultrasound Images under an Optimized Image Processing Algorithm in Guiding the Neurological Safety of Resection of Lumbar Disc Nucleus Pulposus in Spinal Surgery

This study was aimed at investigating the effect of an optimized image processing algorithm in ultrasound images and the influence of resection of lumbar disc nucleus pulposus in spinal surgery under the guidance of ultrasound images on the neurological safety of patients. A total of 60 patients with lumbar disc herniation were selected and divided randomly into the control group and observation group. Patients from the control group were treated with resection of lumbar disc nucleus pulposus by an X-ray-guided foraminal microscope, and patients from the observation group underwent the ultrasound image-guided surgeries with an optimized image processing algorithm. Then, the treatment of patients from the two groups was compared. The results showed that the radiotherapy time in the control group was 120 ± 6.3 min and the radiotherapy dose was 129 ± 10.3 min/sec, while the radiotherapy time in the observation group was 4.5 ± 1.2 min and the radiotherapy dose was 22 ± 7.7 min/sec. The time and dose of radiotherapy in the observation group were significantly lower than those in the control group (P < 0.05). In the control group, the numbers of significant effective cases, effective cases, and ineffective cases were 8, 16, and 6, respectively, while those in the observation group were 12, 18, and 0, respectively. The comparison between the groups showed that the number of effective cases and the number of effective cases in the observation group were significantly higher than those in the control group, and the number of ineffective cases was significantly lower than that in the control group (P < 0.05). In conclusion, ultrasound-guided percutaneous foraminal lumbar discectomy could improve patients' clinical symptoms, promote clinical efficacy, and reduce postoperative pain symptoms, thereby accelerating the postoperative rehabilitation of patients. Moreover, it was extremely safe for the nerves.

Computerized Tomography Image Features under the Reconstruction Algorithm in the Evaluation of the Effect of Ropivacaine Combined with Dexamethasone and Dexmedetomidine on Assisted Thoracoscopic Lobectomy

This research was aimed to study CT image features based on the backprojection filtering reconstruction algorithm and evaluate the effect of ropivacaine combined with dexamethasone and dexmedetomidine on assisted thoracoscopic lobectomy to provide reference for clinical diagnosis. A total of 110 patients undergoing laparoscopic resection were selected as the study subjects. Anesthesia induction and nerve block were performed with ropivacaine combined with dexamethasone and dexmedetomidine before surgery, and chest CT scan was performed. The backprojection image reconstruction algorithm was constructed and applied to patient CT images for reconstruction processing. The results showed that when the overlapping step size was 16 and the block size was 32 × 32, the running time of the algorithm was the shortest. The resolution and sharpness of reconstructed images were better than the Fourier transform analytical method and iterative reconstruction algorithm. The detection rates of lung nodules smaller than 6 mm and 6–30 mm (92.35% and 95.44%) were significantly higher than those of the Fourier transform analytical method and iterative reconstruction algorithm (90.98% and 87.53%; 88.32% and 90.87%) (P < 0.05). After anesthesia induction and lobectomy with ropivacaine combined with dexamethasone and dexmedetomidine, the visual analogue scale (VAS) decreased with postoperative time. The VAS score decreased to a lower level (1.76 ± 0.54) after five days. In summary, ropivacaine combined with dexamethasone and dexmedetomidine had better sedation and analgesia effects in patients with thoracoscopic lobectomy. CT images based on backprojection reconstruction algorithm had a high recognition accuracy for lung lesions.