- 作者列表："Blendowski M","Bouteldja N","Heinrich MP
PURPOSE:Nonlinear multimodal image registration, for example, the fusion of computed tomography (CT) and magnetic resonance imaging (MRI), fundamentally depends on a definition of image similarity. Previous methods that derived modality-invariant representations focused on either global statistical grayscale relations or local structural similarity, both of which are prone to local optima. In contrast to most learning-based methods that rely on strong supervision of aligned multimodal image pairs, we aim to overcome this limitation for further practical use cases. METHODS:We propose a new concept that exploits anatomical shape information and requires only segmentation labels for both modalities individually. First, a shape-constrained encoder-decoder segmentation network without skip connections is jointly trained on labeled CT and MRI inputs. Second, an iterative energy-based minimization scheme is introduced that relies on the capability of the network to generate intermediate nonlinear shape representations. This further eases the multimodal alignment in the case of large deformations. RESULTS:Our novel approach robustly and accurately aligns 3D scans from the multimodal whole-heart segmentation dataset, outperforming classical unsupervised frameworks. Since both parts of our method rely on (stochastic) gradient optimization, it can be easily integrated in deep learning frameworks and executed on GPUs. CONCLUSIONS:We present an integrated approach for weakly supervised multimodal image registration. Achieving promising results due to the exploration of intermediate shape features as registration guidance encourages further research in this direction.
目的: 非线性多模态图像配准，例如，计算机断层扫描 (CT) 和磁共振成像 (MRI) 的融合，从根本上取决于图像相似性的定义。以前导出模态不变表示的方法集中于全局统计灰度关系或局部结构相似性，这两者都倾向于局部最优。与依赖于对齐的多模态图像对的强监督的大多数基于学习的方法相比，我们的目标是为了进一步的实际使用情况而克服这种限制。 方法: 我们提出了一个利用解剖形状信息的新概念，并且只需要对两种模态单独进行分割标记。首先，在标记的CT和MRI输入上联合训练没有跳过连接的形状约束的编码器-解码器分割网络。其次，引入了基于迭代能量的最小化方案，该方案依赖于网络生成中间非线性形状表示的能力。这进一步简化了在大变形的情况下的多模态对准。 结果: 我们的新方法从多模态全心分割数据集中强大和准确地对齐3D扫描，优于经典的无监督框架。由于我们方法的两个部分都依赖于 (随机) 梯度优化，因此它可以很容易地集成在深度学习框架中并在gpu上执行。 结论: 我们提出了一种用于弱监督多模态图像配准的集成方法。由于对中间形状特征的探索，获得了有希望的结果，因为配准指导鼓励了这一方向的进一步研究。
METHODS:OBJECTIVES:The aim was to evaluate the image quality and sensitivity to artifacts of compressed sensing (CS) acceleration technique, applied to 3D or breath-hold sequences in different clinical applications from brain to knee. METHODS:CS with an acceleration from 30 to 60% and conventional MRI sequences were performed in 10 different applications in 107 patients, leading to 120 comparisons. Readers were blinded to the technique for quantitative (contrast-to-noise ratio or functional measurements for cardiac cine) and qualitative (image quality, artifacts, diagnostic findings, and preference) image analyses. RESULTS:No statistically significant difference in image quality or artifacts was found for each sequence except for the cardiac cine CS for one of both readers and for the wrist 3D proton density (PD)-weighted CS sequence which showed less motion artifacts due to the reduced acquisition time. The contrast-to-noise ratio was lower for the elbow CS sequence but not statistically different in all other applications. Diagnostic findings were similar between conventional and CS sequence for all the comparisons except for four cases where motion artifacts corrupted either the conventional or the CS sequence. CONCLUSIONS:The evaluated CS sequences are ready to be used in clinical daily practice except for the elbow application which requires a lower acceleration. The CS factor should be tuned for each organ and sequence to obtain good image quality. It leads to 30% to 60% acceleration in the applications evaluated in this study which has a significant impact on clinical workflow. KEY POINTS:• Clinical implementation of compressed sensing (CS) reduced scan times of at least 30% with only minor penalty in image quality and no change in diagnostic findings. • The CS acceleration factor has to be tuned separately for each organ and sequence to guarantee similar image quality than conventional acquisition. • At least 30% and up to 60% acceleration is feasible in specific sequences in clinical routine.
METHODS:BACKGROUND:The main surgical techniques for spontaneous basal ganglia hemorrhage include stereotactic aspiration, endoscopic aspiration, and craniotomy. However, credible evidence is still needed to validate the effect of these techniques. OBJECTIVE:To explore the long-term outcomes of the three surgical techniques in the treatment of spontaneous basal ganglia hemorrhage. METHODS:Five hundred and sixteen patients with spontaneous basal ganglia hemorrhage who received stereotactic aspiration, endoscopic aspiration, or craniotomy were reviewed retrospectively. Six-month mortality and the modified Rankin Scale score were the primary and secondary outcomes, respectively. A multivariate logistic regression model was used to assess the effects of different surgical techniques on patient outcomes. RESULTS:For the entire cohort, the 6-month mortality in the endoscopic aspiration group was significantly lower than that in the stereotactic aspiration group (odds ratio (OR) 4.280, 95% CI 2.186 to 8.380); the 6-month mortality in the endoscopic aspiration group was lower than that in the craniotomy group, but the difference was not significant (OR=1.930, 95% CI 0.835 to 4.465). A further subgroup analysis was stratified by hematoma volume. The mortality in the endoscopic aspiration group was significantly lower than in the stereotactic aspiration group in the medium (≥40-<80 mL) (OR=2.438, 95% CI 1.101 to 5.402) and large hematoma subgroup (≥80 mL) (OR=66.532, 95% CI 6.345 to 697.675). Compared with the endoscopic aspiration group, a trend towards increased mortality was observed in the large hematoma subgroup of the craniotomy group (OR=8.721, 95% CI 0.933 to 81.551). CONCLUSION:Endoscopic aspiration can decrease the 6-month mortality of spontaneous basal ganglia hemorrhage, especially in patients with a hematoma volume ≥40 mL.
METHODS:OBJECTIVE:The primary purpose of this study was to evaluate the effectiveness of a three-dimensional (3D) software tool (smart planes) for displaying fetal brain planes, and the secondary purpose was to evaluate its accuracy in performing automatic measurements. MATERIAL AND METHODS:This prospective study included singleton fetuses with a gestational age (GA) greater than 18 weeks. Transabdominal two-dimensional ultrasound (2DUS) and 3D smart planes images were respectively used to obtain the basic planes of the fetal brain, with five parameters measured. The images, by either two-dimensional (2D) manual or 3D automatic operation, were reviewed by two experienced sonographers. The agreements between two measurements were analyzed. RESULTS:A total of 226 cases were included. The rates of successful detection by automatic display were as high as 80%. There was substantial agreement between the measurements of the biparietal diameter, head circumference and transcerebellar diameter, but poor agreement between the measurements of cisterna magna and lateral ventricle width. CONCLUSIONS:Smart Planes might be valuable for the rapid evaluation of fetal brain, because it simplifies the evaluation process. However, the technology requires improvement. In addition, this technology cannot replace the conventional manual US scans; it can only be used as an additional approach.