Aiming at the problem of high-quality image reconstruction from projection data at sparse angular views, we proposed an improved fast iterative reconstruction algorithm based on the minimization of selective image total variation (TV). The new reconstruction scheme consists of two components. Firstly, the algebraic reconstruction technique (ART) algorithm was adopted to reconstruct image that met the identity and non-negativity of projection data, and then, secondly, the selective TV minimization was used to modify the above image. Two phases were alternated until it met the convergence criteria. In order to further speed up the convergence of the algorithm, we applied a fast convergence technology in the iterative process. Experiments on simulated Shepp-Logan phantom were carried out. The results demonstrated that the new method not only improved image reconstruction quality and protected the edge of the image characteristics, but also improved the convergence speed of the iterative reconstruction significantly.
Algorithms ; Image Processing, Computer-Assisted ; Phantoms, Imaging ; Tomography, X-Ray Computed

Objective To investigate the clinical value of prenatal MRI in the diagnosis and differential diagnosis of congenital bronchopulmonary sequestration (BPS). Methods From January 2009 to December 2014, 16 fetuses with BPS were diagnosed by fetal MRI in Huzhou Maternity and Child Care Hospital and Shanghai Children′s Medical Center Affiliated to Shanghai Jiaotong University School of Medicine. The clinical data of these cases were analyzed retrospectively. All were singleton pregnancy, and MRI was carried out within 24-48 hours after routine prenatal ultrasound. All the neonates underwent postnatal enhanced CT scan or surgical biopsy after birth, and the results were compared to prenatal MRI diagnosis. Results (1)With prenatal MRI, 16 cases were diagnosed BPS. The lesions located in left lung in 10 cases, and right lung in 6 cases. As the scope of the lesion, 3 cases located in the whole left lung, 6 cases limited to the left lower lobe, and 1 case was subdiaphragmatic on the left side. 2 cases located in the whole right lung and 4 cases limited to the right lower lobe. One case complicated oligoamnios, and one had pleural effusion. Supplying vessels could be found in 14 cases.(2)When the postnatal results were compared with prenatal MRI, 15 cases were comfirmed as BPS (15/16), including 10 intralobar cases 5 extralobar cases. One that was diagnosed as BPS by prenatal MRI was confirmed to be congenital cystic adenomatoid malformation (CCAM) by pathology. The accuracy of prenatal MRI diagnosis of BPS was 15/16. Prenatal ultrasound missed one case and misdiagnosed two cases, as one was mistakened as CCAM and the other as cystic teratoma. Conclusion Prenatal MRI has good clinical value in the diagnosis and differential diagnosis of fetal BPS.

Objective:To establish an automatic segmentation network based on different receptive fields for gross target volume (GTV) and organs at risk in patients with nasopharyngeal carcinoma.Methods:Radiotherapy data of 100 cases of nasopharyngeal carcinoma including CT images and GTV and organs at risk delineated by the physicians were collected. Ninety plans were randomly selected as the training dataset, and the other 10 plans as the validation dataset. Firstly, the images were subject to three data augmentation methods including center cropping, vertical flipping and rotation (-30°to 30°), and then input into MA_net networks proposed in this study for training. The model performance of networks was assessed by the number of network parameters (NP), floating-point number (FPN), the running memory (RM) and Dice index (DI), and eventually compared with DeeplabV3+ , PSP_net, UNet+ + and U_Net networks.Results:When the input image was in the size of 240×240, MA_net had a NP of 23.20%, 20.10%, 25.55% and 27.11% of these 4 networks, 50.02%, 19.86%, 6.37% and 13.44% for the FPN, 40.63%, 23.60%, 11.58% and 14.99% for the RM, respectively. For the DI of GTV, MA_net was 1.16%, 2.28%, 1.27% and 3.59% higher than these 4 networks. For the average DI of GTV and OAR, MA_net was 0.16%, 1.37%, 0.30% and 0.97% higher than these 4 networks.Conclusion:Compared with those four networks, the proposed MA_net network has slightly higher Dice index with fewer parameters, lower FPN and smaller RM.

0.05).There were more polycystic ovary (PCO) and (or) polycystic ovarian syndrome (PCOS) patients,more basal antra] follicles,longer duration of Gn stimulation (range 16-33 days),higher Gn dose,lower serum peak estradiol (E_2) level,fewer oocytes,fewer embryos transferred,in group 1 compared with group 2 (P

OBJECTIVEWe propose a new iterative reconstruction method based on split-Bregman method with tight frame regularization for effective and accurate reconstruction of the sparse-view cone beam CT image.

METHODSA tight frame was chosen as the regularization term for the objective function, so that the image reconstruction involves only the minimization of an objective function according to the compressed sensing theory. We utilized the split-Bregman method to tackle the task of minimization in three steps: (1) a fast calculation of the forward projection matrix; (2) introducing an intermediate variable to transform the non-differentiated L1 regularization term into the differentiated L2 regularization problem, and solving the target function using conjugate-gradient method; (3) updating the intermediate variable using shrinkage formula from Bregman method.

RESULTSDigital and physical phantom experimental results suggested that our new approach had great advantages in terms of image quality, reconstruction time, and applicability.

CONCLUSIONThe proposed method can accurately reconstruct CBCT image with limited data to lower the X-ray dose and accelerate the calculation speed in comparison with the POCS method.

An algebraic image reconstruction from few views using bilateral-filtering iterative method was proposed due to the problem of computed tomography insufficient data in the present study. In each iteration reconstruction, we first used algebraic reconstruction technique (ART) algorithm to reconstruct an image, ensuring the non-negativity of the reconstructed image at the same time, and then performed bilateral-filtering to the above-mentioned image. In order to improve reconstructed image quality and accelerate the convergence speed, we developed a modified bilateral-filtering method. Shepp-Logan simulation experiments and real CT projection data reconstructions showed the feasibility of the algorithm. The results showed that, compared with the traditional methods of filtered back projection (FBP), ART and GF-ART,the proposed method has a higher signal-to-noise ratio, and maintains more effectively the image edge information.
Algorithms ; Artifacts ; Humans ; Image Processing, Computer-Assisted ; methods ; Radiographic Image Interpretation, Computer-Assisted ; methods ; Tomography, X-Ray Computed ; methods

OBJECTIVETo propose a new method for effectively and rapidly removing the ring artifacts in CT images based on image post-processing.

METHODSThe CT image with ring artifacts in the Cartesian coordinate was first transformed into an image with line artifacts in the polar coordinate. The image in the polar coordinate was then filtered by designing a one-dimensional filter to calculate the mean and variance of each pixel after filtering, which were compared with the variance threshold value and the pixel threshold value to determine the position of the artifacts for corrections accordingly. Finally, the polar coordinate image was converted into Cartesian coordinate image.

RESULTSSimulated and actual CT data experimental results demonstrated the efficiency of this method for removing artifacts, retaining the image fidelity and reducing the processing time.

CONCLUSIONThe new method can accurately recognize the position of the artifacts and effectively remove them to facilitate the clinical diagnosis.

Objective To explore the value of prenatal MRI in the diagnosis of fetal simple expansion of lateral ventricle(ventriculomegaly), and follow up the nervous system development status after birth. Methods Simple expansion of the lateral ventricle fetus by prenatal MRI examination were collected in Huzhou Maternal and Child Care Hospital from May 2013 to June 2015, 126 cases of live births in expansion group, 50 normal cases were recruited in the same period as the control group. In expansion group, fetal subgroup analysis was done:(1) unilateral or bilateral lateral ventricle expasion:one group was 98 cases was lateral ventricle expansion (77.8%, 98/126), expansion of bilateral ventricle group was 28 cases (22.2%, 28/126). (2) Prenatal MRI in the diagnosis of the lateral ventricle of expansion: expansion of the lateral ventricle width was greater than 10.0 mm, if both sides were expanding, the expand width was the heavier one side, divided into 3 subgroups: ①Expansion in group A (lateral ventricle width 10.0-12.0 mm) were 88 cases (69.8%, 88/126).②Expansion in group B (lateral ventricle width 12.1-15.0 mm) were 29 cases (23.0%, 29/126). ③Expansion of group C (lateral ventricle width> 15.0 mm) were 9 cases (7.12%, 9/126). All 176 cases were followed up after birth at the 3rd, 6th, 12th, 18th month (corrected age was used for premature babies), and Gesell developmental schedules (GDS) were used to evaluate the neurobehavioral development. Results (1) The MRI results after birth:21 cases were followed up by MRI after birth. In group A, 11 cases had MRI and 9 were normal (the ventricular width<10.0 mm after birth) , the other 2 cases were stable (the ventricular width measured first time after birth was ≥10.0 mm, but the difference was within 2.0 mm from the MRI before birth). In group B, 4 cases had MRI, 1 was normal, 1 was stable, and 2 cases were getting better (the ventricular width measured first time after birth was ≥10.0 mm, but the width decreased more than 2.0 mm from the MRI before birth). In group C, 6 cases had MRI. 3 cases were getting better and 3 cases were stable. (2) Overall GDS results:expansion group after the birth of the 3rd, 6th, 12th, 18th month GDS evaluation results compared with control group, respectively, the differences were not statistically significant (all P>0.05). (3) The GDS results among the subgroups:in each evaluation after birth, there were no statistically significant differences between group A and the control group (all P>0.05). The GDS results of group B at the 3rd and 6th month were lower than those of the control group (P<0.05); while there were no statistically significant differences between the 2 goups at the 12th and 18th month (P>0.05). And for group C, statistically significant differences were found compared to the control group at each follow-up time (all P<0.05). (4) GDS results at different times after birth in the expansion group:there was no statistically significant difference between the results at the 3rd and 6th month (P>0.05). But when the result at the 3rd month was compared to the results of the 12th or 18th month, the differences were statistically significant (P<0.05). GDS result of 6th months after birth compared with 12th and 18th months, respectively, there were no statistically significant differences (P>0.05). There was no statistically significant difference between the results at the 12th and 18th month (P>0.05). (5) The GDS results in unilateral and bilateral ventricle expansion:at the 18th month, among the 98 unilateral cases, 86 (87.8%, 86/98) had normal GDS results(>85 scores);8 (8.2%, 8/98) had borderline results (75-85 scores);4 (4.1%, 4/98) had delayed results (<75 scores). Among the 28 bilateral cases, 23 (82.1%, 23/28) had normal GDS results;3 (10.7%, 3/28) had borderline results; 2 (7.1%, 2/28) had delayed results. There was no statistically significant difference (P>0.05). Conclusions Among the simple expansion of lateral ventricle, those whose ventricular width are≤12.0 mm may not need clinical treatment. If the width is between 12.1 to 15.0 mm, closely follow-up and targeted rehabilitation training after birth are recommended. When the width is more than 15.0 mm, the risk of the central nervous system function delay is significantly increased, and early intervention might improve the prognosis.

Objective:To establish a correlation model between MRI and CT images to generate synthetic-CT (sCT) of head and neck cancer during MRI-guided radiotherapy by using generative adversarial networks (GAN).Methods:Images and IMRT plans of 45 patients with nasopharyngeal carcinoma were collected before treatment. Firstly, the MRI (T1) and CT images were preprocessed, including rigid registration, clipping, background removal and data enhancement, etc. Secondly, the cases were trained by GAN, of which 30 cases were randomly selected and put into the network as training set images for modeling and learning, and the other 15 cases were used for testing. The image quality of predicted sCT and real CT were statistically compared, and the dose distribution recalculated upon predicted sCT was statistically compared with that of real planned dose distribution.Results:The mean absolute error of the predicted sCT of the testing set was (79.15±11.37) HU, and the SSIM value was 0.83±0.03. The MAE values of dose distribution difference at different regional levels were less than 1% compared to the prescription dose. The gamma passing rate of the sCT dose distribution was higher than 92% and 98% under the 2mm/2% and 3mm/3% criteria.Conclusions:We have successfully proposed and realized the generation of sCT for head and neck cancer using GAN, which lays a foundation for the implementation of MRI-guided radiotherapy. The comparison of image quality and dosimetry shows the feasibility and accuracy of this method.

Objective:To compare the accuracy and generalized robustness of three predictive models of knowledge-based treatment strategies for radiotherapy for optimized model selection.Methods:The clinical radiotherapy plans of 45 prostate cancer (PC) cases and 25 nasopharyngeal cancer (NPC) cases were collected, and analyzed using three models (Z, L and S model), proposed by Zhu et al, Appenzoller et al and Shiraishi et al, respectively, to predict the dose-volume histogram (DVH) of bladder and rectum on PC cases and that of left and right parotid on NPC cases. The prediction error was measured by the difference of area under the predicted DVH and the clinical DVH curves (|V (pre_DVH)-V (clin_DVH)|), where a smaller prediction error implies a greater prediction accuracy. The accuracies of these three models were compared on the single organ at risk (OAR), and the generalized robustness of models was evaluated and compared by calculating the standard deviation of the prediction accuracy on different OAR. Results:For bladder and rectum, the prediction error of L model (0.114 and 0.163, respectively) was significantly higher than those values of Z and S models (≤0.071, P<0.05); for left parotid gland, the predicted error of S model (0.033) did not present significant difference from those values of Z and L models (≤0.025, P>0.05); for right parotid gland, S model (0.033) demonstrated significantly higher prediction error than those of Z and L models (≤0.028, P<0.05). Regarding different OAR, S model showed a lower standard deviation of prediction accuracy when comparing to Z and L models (0.016, 0.018 and 0.060, respectively). Conclusions:In the prediction of DVH in bladder and rectum of PC, Z and S models were more accurate than L model. In contrast, Z and L models demonstrated higher accuracy than S model in the prediction of left and right parotid glands of NPC. In respect to different OAR, the generalized robustness of S model was superior than the other two models.