Registration of serial images plays an increasingly important role in medicine. A novel registration method used for serial images matching is proposed, which is based on the joint histogram. After thresholding the two images to be registered, the joint histogram is divided into four separate regions. Then the criterion function is defined as bin counting in a specific region of the joint histogram, which simplifies the computation of the criteria function greatly and speeds up the alignment process significantly. We choose the Powell optimization algorithm to calculate the registration parameters. The comparison of the results from both mutual information and our method shows that the new method based on segmentation and counting is a fast, simple, efficient and accurate registration method.

Based on a discussion on PACS and the way its image workstation obtains scanned sequential images, this paper presented a method of 3D surface construction and visualization on PACS workstation. Guest/Server structure was used between PACS application entities. Image storing and transmission were realized by service classes established by DICOM standards. Relation database was used to arrange the stored sequential images. Image workstation transformed the sequential images obtained from PACS net into volume data field. 3D reconstruction and rendering results were obtained by using surface-rendering and volume-rendering methods, which made the 3D construction results acquire vivid 3D structure details of high fidelity and strong sense of reality. 3 sets of application results were also presented in this paper.
Humans ; Image Processing, Computer-Assisted ; methods ; Imaging, Three-Dimensional ; Magnetic Resonance Imaging ; Radiology Information Systems ; Tomography, X-Ray Computed ; User-Computer Interface

OBJECTIVETo study the effect of NOD2 on colitis pathogenesis in experimental rats, and discuss therapeutical effect and mechanism of kushenin injection (OMT) on colitis in experimental rats.

METHODFourty Sprague-Dawley (SD) rats were randomly divided into four groups: the normal control group, the model group, the SASP group, and the OMT group, with 10 rats in each group. Except the normal control group, models were established in the remaining three groups with TNBS. The OMT group was injected with kushenin injection, the SASP group was orally administered with mesalazine suspension, the model group and the normal group were orally administered with distilled water for 15 days. Colon lesion score and histological score of experimental rats were observed. Expression of NOD2, NF-kappaB p65 protein in rats colonic mucous was detected by immunohistochemistry. Expression of IL-6 in rat colon mucous was detected by ELISA.

RESULTCompared with normal control group, the expression of NOD2, NF-kappaB p65 and IL-6 in colonic mucosa of the model group were significantly increased (P < 0.01). The SASP group and the OMT group showed lower expressions of NOD2, NF-kappaB p65 and IL-6 in colonic mucosa than the model group (P < 0.01, P < 0.05).

CONCLUSIONThe over expression of colonic mucosa proteins NOD2 and NF-kappaB p65 and increasing secretion of IL-6 take part in the appearance and development of ulcerative colitis. OMT can attenuate ulcerative colitis and protect colonic mucosa by inhibiting expression of NOD2, NF-kappaB p65 and decreasing IL-6.

Animals ; Colitis ; metabolism ; pathology ; physiopathology ; prevention & control ; Colon ; drug effects ; metabolism ; pathology ; physiopathology ; Eating ; drug effects ; Gene Expression Regulation ; drug effects ; Injections ; Intestinal Mucosa ; drug effects ; metabolism ; pathology ; physiopathology ; Male ; Nod2 Signaling Adaptor Protein ; metabolism ; Organ Size ; drug effects ; Pterocarpans ; administration & dosage ; pharmacology ; Rats ; Rats, Sprague-Dawley ; Transcription Factor RelA ; metabolism

Discrimination of abnormal images from the numerous wireless capsule endoscope (WCE) video sequence images is laborious and time-consuming, so that a computer-based automatic image recognition system is desired for this task. We propose an algorithm to allow feature extraction from each image channel and decision fusion using multiple BP neural networks. The algorithm was tested and the results demonstrated its high efficiency and accuracy in identification of abnormalities in the WCE images.
Algorithms ; Capsule Endoscopy ; methods ; Image Interpretation, Computer-Assisted ; methods ; Pattern Recognition, Automated ; methods

Objective To explore the topological properties of the brain structural network in patients with neuromyelitis optica spectrum disorder (NMOSD).Methods Diffusion tensor imaging was performed in 41 NMOSD patients (patient group) and 40 age-and sex-matched healthy volunteers (control group) who were admitted to the Department of Neurology,The Third Affiliated Hospital to Sun Yat-sen University from September 2014 to October 2017.The deterministic fiber tracking techniques were used to construct the white matter structural weighted network.Topological properties of the brain structural network were then calculated based on complex graph theory analysis.The 2 groups were compared in terms of global and local parameters of the brain structural network using statistical methods.Results The brain structural networks in both groups exhibited small world properties.Compared with the control group,the global efficiency of the brain structural network in the patient group was significantly decreased and the shortest path length significantly increased (P=0.002,P=0.002,FDR correction).There were no statistically significant differences between the brain structural networks of the 2 groups in terms of clustering coefficient,the shortest path length on average,value of small world property,average clustering coefficient or local efficiency (P=0.780,P=0.496,P=0.279,P=0.269,P=0.050,FDR correction).Compared with the control group,the nodal efficiency of the brain structural network of the patient group was significantly decreased in the frontal lobe (bilateral precentral gyrus,middle frontal gyrus of the right orbital part,inferior frontal gyrus of the right opercular part,right rolandic operculum,bilateral median cingulate and paracingulate gyri),parietal lobe (right posterior cingulate gyrus,right superior parietal gyrus,left inferior parietal of angular gyri,right angle gyrus,and right precuneus),temporal lobe (bilateral hippocampus and right parahippocampal gyrus),occipital lobe (left cuneus,left superior occipital gyms,bilateral middle occipital gyrus,and left inferior occipital gyrus) and subcortical region (right caudate nucleus and right thalamus) (P＜0.05,FDR correction).Conclusion There is abnormal connection in brain structural network in NMOSD patients.

OBJECTIVETo simulate the multi-leaf collimator of Varian linear accelerator using Monte Carlo method.

METHODSThe multi-leaf collimator model was established using the DYNVMLC module of BEAMnrc and validated by comparison of Monte Carlo simulation and actual measurement results.

RESULTSThe simulation results were well consistent with the actual measurement results with a bias of less than 3%.

CONCLUSIONThe multi-leaf collimator of Varian linear accelerator can be successfully modeled using Monte Carlo method for analysis of the impact of the geometric properties of the multi-leaf collimator on the dose distribution.

Humans ; Models, Theoretical ; Monte Carlo Method ; Particle Accelerators ; Radiotherapy Dosage ; Radiotherapy Planning, Computer-Assisted

It is an important morphological research method to reconstruct the 3D imaging from serial section tissue images. Registration of serial images is a key step to 3D reconstruction. Firstly, an introduction to the segmentation-counting registration algorithm is presented, which is based on the joint histogram. After thresholding of the two images to be registered, the criterion function is defined as counting in a specific region of the joint histogram, which greatly speeds up the alignment process. Then, the method is used to conduct the serial tissue image matching task, and lies a solid foundation for 3D rendering. Finally, preliminary surface rendering results are presented.
Algorithms ; Image Processing, Computer-Assisted ; methods ; Imaging, Three-Dimensional ; Microtomy ; methods

Radiographic detection of pulmonary nodules based on three-dimensional Hessian matrix is highly sensitive but frequently produces false positive results in areas where blood vessels intersect. We propose a novel approach to pulmonary nodule detection using Hessian matrix-based adaptive window structure analysis, in which the structure coefficients is used to differentiate a voxel that belongs to a nodule or vascular structures, followed by construction of the 3D adaptive window to analyze the local structure characteristics; the nodules were then detected using the discrimination function. The experimental results on pulmonary CT images from 17 patients showed a 100% detection sensitivity for nodules of varying sizes and types, with also significantly reduced false positive results generated by the vessel junctions. This approach provides valuable assistance to follow-up positioning and segmentation of the pulmonary nodules.
Humans ; Lung ; pathology ; Lung Neoplasms ; diagnosis ; Tomography, X-Ray Computed

Elastic registration of medical image is an important subject in medical image processing. Previous work has concentrated on selecting the corresponding landmarks manually and then using thin-plate spline interpolating to gain the elastic transformation. However, the landmarks extraction is always prone to error, which will influence the registration results. Localizing the landmarks manually is also difficult and time-consuming. We the optimization theory to improve the thin-plate spline interpolation, and based on it, used an automatic method to extract the landmarks. Combining these two steps, we have proposed an automatic, exact and robust registration method and have gained satisfactory registration results.
Algorithms ; Image Processing, Computer-Assisted ; methods ; Magnetic Resonance Imaging

We proposed a new stitching method based on sift features to obtain an enlarged view of transmission electron microscopic (TEM) images with a high resolution. The sift features were extracted from the images, which were then combined with fitted polynomial correction field to correct the images, followed by image alignment based on the sift features. The image seams at the junction were finally removed by Poisson image editing to achieve seamless stitching, which was validated on 60 local glomerular TEM images with an image alignment error of 62.5 to 187.5 nm. Compared with 3 other stitching methods, the proposed method could effectively reduce image deformation and avoid artifacts to facilitate renal biopsy pathological diagnosis.
Algorithms ; Artifacts ; Humans ; Image Processing, Computer-Assisted ; methods ; Kidney Glomerulus ; ultrastructure ; Microscopy, Electron, Transmission ; methods