In thefield of diagnosis of medical images the challenge lies in tracking and identifying the defective cells and the extent of the defective region within the complex structure of a brain cavity.Locating the defective...In thefield of diagnosis of medical images the challenge lies in tracking and identifying the defective cells and the extent of the defective region within the complex structure of a brain cavity.Locating the defective cells precisely during the diagnosis phase helps tofight the greatest exterminator of mankind.Early detec-tion of these defective cells requires an accurate computer-aided diagnostic system(CAD)that supports early treatment and promotes survival rates of patients.An ear-lier version of CAD systems relies greatly on the expertise of radiologist and it con-sumed more time to identify the defective region.The manuscript takes the efficacy of coalescing features like intensity,shape,and texture of the magnetic resonance image(MRI).In the Enhanced Feature Fusion Segmentation based classification method(EEFS)the image is enhanced and segmented to extract the prominent fea-tures.To bring out the desired effect the EEFS method uses Enhanced Local Binary Pattern(EnLBP),Partisan Gray Level Co-occurrence Matrix Histogram of Oriented Gradients(PGLCMHOG),and iGrab cut method to segment image.These prominent features along with deep features are coalesced to provide a single-dimensional fea-ture vector that is effectively used for prediction.The coalesced vector is used with the existing classifiers to compare the results of these classifiers with that of the gen-erated vector.The generated vector provides promising results with commendably less computatio nal time for pre-processing and classification of MR medical images.展开更多
This article proposes a novel method to fuse infrared and visible light images based on region segmentation. Region segmen-tation is used to determine important regions and background information in the input image. T...This article proposes a novel method to fuse infrared and visible light images based on region segmentation. Region segmen-tation is used to determine important regions and background information in the input image. The non-subsampled contourlet transform (NSCT) provides a flexible multiresolution,local and directional image expansion,and also a sparse representation for two-dimensional (2-D) piecewise smooth signal building images,and then different fusion rules are applied to fuse the NSCT coefficients fo...展开更多
Data fusion is usually an important process in multi-sensor remotely sensed imagery integration environments with the aim of enriching features lacking in the sensors involved in the fusion process. This technique has...Data fusion is usually an important process in multi-sensor remotely sensed imagery integration environments with the aim of enriching features lacking in the sensors involved in the fusion process. This technique has attracted much interest in many researches especially in the field of agriculture. On the other hand, deep learning (DL) based semantic segmentation shows high performance in remote sensing classification, and it requires large datasets in a supervised learning way. In the paper, a method of fusing multi-source remote sensing images with convolution neural networks (CNN) for semantic segmentation is proposed and applied to identify crops. Venezuelan Remote Sensing Satellite-2 (VRSS-2) and the high-resolution of Google Earth (GE) imageries have been used and more than 1000 sample sets have been collected for supervised learning process. The experiment results show that the crops extraction with an average overall accuracy more than 93% has been obtained, which demonstrates that data fusion combined with DL is highly feasible to crops extraction from satellite images and GE imagery, and it shows that deep learning techniques can serve as an invaluable tools for larger remote sensing data fusion frameworks, specifically for the applications in precision farming.展开更多
To overcome the shortcomings of 1 D and 2 D Otsu’s thresholding techniques, the 3 D Otsu method has been developed.Among all Otsu’s methods, 3 D Otsu technique provides the best threshold values for the multi-level ...To overcome the shortcomings of 1 D and 2 D Otsu’s thresholding techniques, the 3 D Otsu method has been developed.Among all Otsu’s methods, 3 D Otsu technique provides the best threshold values for the multi-level thresholding processes. In this paper, to improve the quality of segmented images, a simple and effective multilevel thresholding method is introduced. The proposed approach focuses on preserving edge detail by computing the 3 D Otsu along the fusion phenomena. The advantages of the presented scheme include higher quality outcomes, better preservation of tiny details and boundaries and reduced execution time with rising threshold levels. The fusion approach depends upon the differences between pixel intensity values within a small local space of an image;it aims to improve localized information after the thresholding process. The fusion of images based on local contrast can improve image segmentation performance by minimizing the loss of local contrast, loss of details and gray-level distributions. Results show that the proposed method yields more promising segmentation results when compared to conventional1 D Otsu, 2 D Otsu and 3 D Otsu methods, as evident from the objective and subjective evaluations.展开更多
Study Design: This is a retrospective cohort study using data from the adult spinal deformity (ASD) database of a single institution. Purpose: To investigate the incidence of proximal junctional failure and distal jun...Study Design: This is a retrospective cohort study using data from the adult spinal deformity (ASD) database of a single institution. Purpose: To investigate the incidence of proximal junctional failure and distal junctional failure (DJF) after ASD surgery with a lower instrumented vertebra (LIV) at L5. Overview of Literature: Spinopelvic fixation from the lower thoracic vertebra to the pelvis is the current gold standard treatment for ASD. However, the LIV at L5 is acceptable in some cases. Methods: Fifty-six patients who underwent corrective surgery for ASD with LIV at L5 were included. The upper instrumented vertebra (UIV) was T7 in one patient, T9 in 14, T10 in three, T11 in four, T12 in eight, L1 in 10, and L2 in 16. Regarding clinical parameters, age, sex, curve types of Scoliosis Research Society-Schwab classification, number of levels fused, follow-up period, hip bone mallow density, revision surgery rate, and radiographic measurements were compared between the T (UIV: T7 - 10) and TL (UIV: T11 - L2) groups. Results: The revision surgery rate was 19.6% overall. In the T and TL groups, it was 27.8%, and 15.8%, respectively (p = 0.305). The rate of DJF in the T group (33.3%) was significantly higher than in the TL group (5.3%). The rate of proximal junctional kyphosis in the T group (55.6%) was higher than in the TL group (28.9%), with no significant difference. The mean global alignment, sagittal vertical axis, and C7 plumb line-central sacral vertical line were not different between both groups. Conclusions: ASD surgery with LIV set at L5 and UIV set at the thoracic vertebrae (T7 - T10) has a risk of adjacent segment disease.展开更多
Objectives: To investigate the effect of lumbar interbody fusion via the oblique lateral approach (OLIF) in the treatment of single level lumbar spondylolisthesis. Methods: Retrospective analysis was made on 32 cases ...Objectives: To investigate the effect of lumbar interbody fusion via the oblique lateral approach (OLIF) in the treatment of single level lumbar spondylolisthesis. Methods: Retrospective analysis was made on 32 cases of single level lumbar spondylolisthesis treated by lumbar interbody fusion via the oblique lateral approach from July 2020 to July 2021. 14 males and 18 females;the age was (66.5 ± 11.5) years (55 - 82 years). 1) The operation time, intraoperative blood loss and complications were recorded;2) the scores of visual analog scale. VAS and Oswestry disability index (ODI) of low back pain and lower limb pain were collected before operation and at the last follow-up;by observing the imaging data, the height of the intervertebral space, the anterior convex angle of the intervertebral space, the anterior convex angle of the lumbar spine, the sagittal diameter of the dural sac and the spondylolisthesis were measured. Results: All patients successfully completed the operation, the average operation time was (103.9 ± 21.1) min, the average intraoperative bleeding volume was (72.3 ± 16.4) ml. There was no vascular injury during the operation, no infection occurred in all surgical incisions, and Class I/A healing was achieved. The VAS scores of low back pain and leg pain before operation and at the last follow-up were lower than those before operation, and the difference was statistically significant (P < 0.05);the ODI at the last follow-up was lower than that before operation, and the difference was statistically significant (P < 0.05). At the last follow-up, the height of intervertebral space, the height of intervertebral foramen and the sagittal diameter of dural sac were greater than those before operation, with statistically significant differences (P < 0.05);the spondylolisthesis rate at the last follow-up was lower than that before operation, with a statistically significant difference (P < 0.05). Left thigh surface numbness occurred in 2 cases (6.3%) and disappeared after 1 week;Hip flexion weakness occurred in 1 case (0.03%), which recovered after 12 days;there were no complications such as retroperitoneal hematoma, ureteral injury, retrograde ejaculation, intestinal and lumbar plexus injury. Conclusion: The early clinical effect of OLIF in the treatment of single level lumbar spondylolisthesis is significant. This surgical method is minimally invasive, safe and effective, which can significantly reduce the amount of intraoperative bleeding and reduce the risk of postoperative complications. Its main working principle is to make the annulus fibrosus, posterior longitudinal ligament and ligamentum flavum shrink and recover the height of the intervertebral space through decompression, loosening and stretching of the intervertebral space, so as to achieve the reduction of the slipped vertebral body, increase the height of the intervertebral foramen Enlarge the spinal canal volume and eliminate dynamic compression to play an indirect decompression role, improve the symptoms of low back and leg pain, and reconstruct the stability of the spine through interbody fusion.展开更多
Knowledge-based multi-feaure-fusion and multi-resolution analysis is for adapive image segment -ation and experimental results show it can be used to extraot targets from complicated backgcround with the help of Prior...Knowledge-based multi-feaure-fusion and multi-resolution analysis is for adapive image segment -ation and experimental results show it can be used to extraot targets from complicated backgcround with the help of Priorknowledge and artificial intelligence.展开更多
The volume of hippocampal subfields is closely related with early diagnosis of Alzheimer's disease.Due to the anatomical complexity of hippocampal subfields,automatic segmentation merely on the content of MR image...The volume of hippocampal subfields is closely related with early diagnosis of Alzheimer's disease.Due to the anatomical complexity of hippocampal subfields,automatic segmentation merely on the content of MR images is extremely difficult.We presented a method which combines multi-atlas image segmentation with extreme learning machine based bias detection and correction technique to achieve a fully automatic segmentation of hippocampal subfields.Symmetric diffeomorphic registration driven by symmetric mutual information energy was implemented in atlas registration,which allows multi-modal image registration and accelerates execution time.An exponential function based label fusion strategy was proposed for the normalized similarity measure case in segmentation combination,which yields better combination accuracy.The test results show that this method is effective,especially for the larger subfields with an overlap of more than 80%,which is competitive with the current methods and is of potential clinical significance.展开更多
文摘In thefield of diagnosis of medical images the challenge lies in tracking and identifying the defective cells and the extent of the defective region within the complex structure of a brain cavity.Locating the defective cells precisely during the diagnosis phase helps tofight the greatest exterminator of mankind.Early detec-tion of these defective cells requires an accurate computer-aided diagnostic system(CAD)that supports early treatment and promotes survival rates of patients.An ear-lier version of CAD systems relies greatly on the expertise of radiologist and it con-sumed more time to identify the defective region.The manuscript takes the efficacy of coalescing features like intensity,shape,and texture of the magnetic resonance image(MRI).In the Enhanced Feature Fusion Segmentation based classification method(EEFS)the image is enhanced and segmented to extract the prominent fea-tures.To bring out the desired effect the EEFS method uses Enhanced Local Binary Pattern(EnLBP),Partisan Gray Level Co-occurrence Matrix Histogram of Oriented Gradients(PGLCMHOG),and iGrab cut method to segment image.These prominent features along with deep features are coalesced to provide a single-dimensional fea-ture vector that is effectively used for prediction.The coalesced vector is used with the existing classifiers to compare the results of these classifiers with that of the gen-erated vector.The generated vector provides promising results with commendably less computatio nal time for pre-processing and classification of MR medical images.
基金National Natural Science Foundation of China (60802084)
文摘This article proposes a novel method to fuse infrared and visible light images based on region segmentation. Region segmen-tation is used to determine important regions and background information in the input image. The non-subsampled contourlet transform (NSCT) provides a flexible multiresolution,local and directional image expansion,and also a sparse representation for two-dimensional (2-D) piecewise smooth signal building images,and then different fusion rules are applied to fuse the NSCT coefficients fo...
文摘Data fusion is usually an important process in multi-sensor remotely sensed imagery integration environments with the aim of enriching features lacking in the sensors involved in the fusion process. This technique has attracted much interest in many researches especially in the field of agriculture. On the other hand, deep learning (DL) based semantic segmentation shows high performance in remote sensing classification, and it requires large datasets in a supervised learning way. In the paper, a method of fusing multi-source remote sensing images with convolution neural networks (CNN) for semantic segmentation is proposed and applied to identify crops. Venezuelan Remote Sensing Satellite-2 (VRSS-2) and the high-resolution of Google Earth (GE) imageries have been used and more than 1000 sample sets have been collected for supervised learning process. The experiment results show that the crops extraction with an average overall accuracy more than 93% has been obtained, which demonstrates that data fusion combined with DL is highly feasible to crops extraction from satellite images and GE imagery, and it shows that deep learning techniques can serve as an invaluable tools for larger remote sensing data fusion frameworks, specifically for the applications in precision farming.
文摘To overcome the shortcomings of 1 D and 2 D Otsu’s thresholding techniques, the 3 D Otsu method has been developed.Among all Otsu’s methods, 3 D Otsu technique provides the best threshold values for the multi-level thresholding processes. In this paper, to improve the quality of segmented images, a simple and effective multilevel thresholding method is introduced. The proposed approach focuses on preserving edge detail by computing the 3 D Otsu along the fusion phenomena. The advantages of the presented scheme include higher quality outcomes, better preservation of tiny details and boundaries and reduced execution time with rising threshold levels. The fusion approach depends upon the differences between pixel intensity values within a small local space of an image;it aims to improve localized information after the thresholding process. The fusion of images based on local contrast can improve image segmentation performance by minimizing the loss of local contrast, loss of details and gray-level distributions. Results show that the proposed method yields more promising segmentation results when compared to conventional1 D Otsu, 2 D Otsu and 3 D Otsu methods, as evident from the objective and subjective evaluations.
文摘Study Design: This is a retrospective cohort study using data from the adult spinal deformity (ASD) database of a single institution. Purpose: To investigate the incidence of proximal junctional failure and distal junctional failure (DJF) after ASD surgery with a lower instrumented vertebra (LIV) at L5. Overview of Literature: Spinopelvic fixation from the lower thoracic vertebra to the pelvis is the current gold standard treatment for ASD. However, the LIV at L5 is acceptable in some cases. Methods: Fifty-six patients who underwent corrective surgery for ASD with LIV at L5 were included. The upper instrumented vertebra (UIV) was T7 in one patient, T9 in 14, T10 in three, T11 in four, T12 in eight, L1 in 10, and L2 in 16. Regarding clinical parameters, age, sex, curve types of Scoliosis Research Society-Schwab classification, number of levels fused, follow-up period, hip bone mallow density, revision surgery rate, and radiographic measurements were compared between the T (UIV: T7 - 10) and TL (UIV: T11 - L2) groups. Results: The revision surgery rate was 19.6% overall. In the T and TL groups, it was 27.8%, and 15.8%, respectively (p = 0.305). The rate of DJF in the T group (33.3%) was significantly higher than in the TL group (5.3%). The rate of proximal junctional kyphosis in the T group (55.6%) was higher than in the TL group (28.9%), with no significant difference. The mean global alignment, sagittal vertical axis, and C7 plumb line-central sacral vertical line were not different between both groups. Conclusions: ASD surgery with LIV set at L5 and UIV set at the thoracic vertebrae (T7 - T10) has a risk of adjacent segment disease.
文摘现有的基于深度学习的医学图像分割方法,大多是利用大量的训练数据拟合检测网络,以获得优异的检测性能。这些方法往往需要较大的模型参数,导致检测实时性较差。为此,提出了基于局部上下文引导特征深度融合轻量级医学分割网络(local context guided feature deep fusion lightweight medical segmentation network,LCGML-net)。LCGML-net通过精确的特征选择与特征融合来减少模型拟合所需的参数数量,从而在保证检测精度的同时实现更小的模型参数。在特征提取阶段和映射阶段,分别通过提取和融合目标的多层次多尺度局部上下文特征来丰富特征表达和精准分割。在STARE、CHASEDB1和KITS19等多个基准数据集上开展的实验证明,与其他方法相比,所提出的LCGML-net具有最佳的检测性能和最小的模型参数。
文摘Objectives: To investigate the effect of lumbar interbody fusion via the oblique lateral approach (OLIF) in the treatment of single level lumbar spondylolisthesis. Methods: Retrospective analysis was made on 32 cases of single level lumbar spondylolisthesis treated by lumbar interbody fusion via the oblique lateral approach from July 2020 to July 2021. 14 males and 18 females;the age was (66.5 ± 11.5) years (55 - 82 years). 1) The operation time, intraoperative blood loss and complications were recorded;2) the scores of visual analog scale. VAS and Oswestry disability index (ODI) of low back pain and lower limb pain were collected before operation and at the last follow-up;by observing the imaging data, the height of the intervertebral space, the anterior convex angle of the intervertebral space, the anterior convex angle of the lumbar spine, the sagittal diameter of the dural sac and the spondylolisthesis were measured. Results: All patients successfully completed the operation, the average operation time was (103.9 ± 21.1) min, the average intraoperative bleeding volume was (72.3 ± 16.4) ml. There was no vascular injury during the operation, no infection occurred in all surgical incisions, and Class I/A healing was achieved. The VAS scores of low back pain and leg pain before operation and at the last follow-up were lower than those before operation, and the difference was statistically significant (P < 0.05);the ODI at the last follow-up was lower than that before operation, and the difference was statistically significant (P < 0.05). At the last follow-up, the height of intervertebral space, the height of intervertebral foramen and the sagittal diameter of dural sac were greater than those before operation, with statistically significant differences (P < 0.05);the spondylolisthesis rate at the last follow-up was lower than that before operation, with a statistically significant difference (P < 0.05). Left thigh surface numbness occurred in 2 cases (6.3%) and disappeared after 1 week;Hip flexion weakness occurred in 1 case (0.03%), which recovered after 12 days;there were no complications such as retroperitoneal hematoma, ureteral injury, retrograde ejaculation, intestinal and lumbar plexus injury. Conclusion: The early clinical effect of OLIF in the treatment of single level lumbar spondylolisthesis is significant. This surgical method is minimally invasive, safe and effective, which can significantly reduce the amount of intraoperative bleeding and reduce the risk of postoperative complications. Its main working principle is to make the annulus fibrosus, posterior longitudinal ligament and ligamentum flavum shrink and recover the height of the intervertebral space through decompression, loosening and stretching of the intervertebral space, so as to achieve the reduction of the slipped vertebral body, increase the height of the intervertebral foramen Enlarge the spinal canal volume and eliminate dynamic compression to play an indirect decompression role, improve the symptoms of low back and leg pain, and reconstruct the stability of the spine through interbody fusion.
文摘Knowledge-based multi-feaure-fusion and multi-resolution analysis is for adapive image segment -ation and experimental results show it can be used to extraot targets from complicated backgcround with the help of Priorknowledge and artificial intelligence.
基金Supported by the National Natural Science Foundation of China(Nos.60971133,61271112)
文摘The volume of hippocampal subfields is closely related with early diagnosis of Alzheimer's disease.Due to the anatomical complexity of hippocampal subfields,automatic segmentation merely on the content of MR images is extremely difficult.We presented a method which combines multi-atlas image segmentation with extreme learning machine based bias detection and correction technique to achieve a fully automatic segmentation of hippocampal subfields.Symmetric diffeomorphic registration driven by symmetric mutual information energy was implemented in atlas registration,which allows multi-modal image registration and accelerates execution time.An exponential function based label fusion strategy was proposed for the normalized similarity measure case in segmentation combination,which yields better combination accuracy.The test results show that this method is effective,especially for the larger subfields with an overlap of more than 80%,which is competitive with the current methods and is of potential clinical significance.
