Probabilistic vessel axis tracing and its application to vessel segmentation with stream surfaces and minimum cost paths

We propose a novel framework to segment vessels on their cross-sections. It starts with a probabilistic vessel axis tracing in a gray-scale three-dimensional angiogram, followed by vessel boundary delineation on cross-sections derived from the extracted axis. It promotes a more intuitive delineation of vessel boundaries which are mostly round on the cross-sections. The prior probability density function of the axis tracer's formulation permits seamless integration of user guidance to produce continuous traces through regions that contain furcations, diseased portions, kissing vessels (vessels in close proximity to each other) and thin vessels. The contour that outlines the vessel boundary in a 3-D space is determined as the minimum cost path on a weighted directed acyclic graph derived from each cross-section. The user can place anchor points to force the contour to pass through. The contours obtained are tiled to approximate the vessel boundary surface. Since we use stream surfaces generated w.r.t. the traced axis as cross-sections, non-intersecting adjacent cross-sections are guaranteed. Therefore, the tiling can be achieved by joining vertices of adjacent contours. The vessel boundary surface is then deformed under constrained movements on the cross-sections and is voxelized to produce the final vascular segmentation. Experimental results on synthetic and clinical data have shown that the vessel axes extracted by our tracer are continuous and less jittered as compared with the other two trace-based algorithms. Furthermore, the segmentation algorithm with cross-sections are robust to noise and can delineate vessel boundaries that have level of variability similar to those obtained manually.     

A review of machine learning methods for retinal blood vessel segmentation and artery/vein classification

The eye affords a unique opportunity to inspect a rich part of the human microvasculature non-invasively via retinal imaging. Retinal blood vessel segmentation and classification are prime steps for the diagnosis and risk assessment of microvascular and systemic diseases. A high volume of techniques based on deep learning have been published in recent years. In this context, we review 158 papers published between 2012 and 2020, focussing on methods based on machine and deep learning (DL) for automatic vessel segmentation and classification for fundus camera images. We divide the methods into various classes by task (segmentation or artery-vein classification), technique (supervised or unsupervised, deep and non-deep learning, hand-crafted methods) and more specific algorithms (e.g. multiscale, morphology). We discuss advantages and limitations, and include tables summarising results at-a-glance. Finally, we attempt to assess the quantitative merit of DL methods in terms of accuracy improvement compared to other methods. The results allow us to offer our views on the outlook for vessel segmentation and classification for fundus camera images.     

Multi-template tensor-based morphometry: application to analysis of Alzheimer's disease

In this paper methods for using multiple templates in tensor-based morphometry (TBM) are presented and compared to the conventional single-template approach. TBM analysis requires non-rigid registrations which are often subject to registration errors. When using multiple templates and, therefore, multiple registrations, it can be assumed that the registration errors are averaged and eventually compensated. Four different methods are proposed for multi-template TBM. The methods were evaluated using magnetic resonance (MR) images of healthy controls, patients with stable or progressive mild cognitive impairment (MCI), and patients with Alzheimer's disease (AD) from the ADNI database (N=772). The performance of TBM features in classifying images was evaluated both quantitatively and qualitatively. Classification results show that the multi-template methods are statistically significantly better than the single-template method. The overall classification accuracy was 86.0% for the classification of control and AD subjects, and 72.1% for the classification of stable and progressive MCI subjects. The statistical group-level difference maps produced using multi-template TBM were smoother, formed larger continuous regions, and had larger t-values than the maps obtained with single-template TBM.     

Atraumatic method of renal blood flow estimation by 133XenoninhaIation and its application to transplanted kidneys

Non-invasive measurement of organ blood flow can be achieved by tracing the elimination patterns of 133Xe administered by inhalation. An adaption of the method for the estimation of renal blood flow was developed. The 133Xe is accumulated in the tissue by re-breathing for 1 min and the time course of its washout from the kidney is followed for 14 min thereafter. Normal values were determined in ten dogs and forty-five healthy human volunteers. In man they were similar to results obtained with 131I-hippuran clearance. When flow rates were between 250 and 600 ml/100 g/min the correlation coefficient was 0.84. Only in cases with high cortex flow rates (greater than 600 ml/100 g/min) did the inhalation method give values higher than those determined by the 131I-hippuran clearance. In dogs the results closely correlated with results obtained by direct intra arterial xenon injection (r = 0.96). The value of the inhalation method in routine examination of patients with kidney transplants and its suitability for the early detection of ongoing rejection is demonstrated.     

Magnetic resonance angiography: from anatomical knowledge modeling to vessel segmentation

Magnetic resonance angiography (MRA) has become a common way to study cerebral vascular structures. Indeed, it enables to obtain information on flowing blood in a totally non-invasive and non-irradiant fashion. MRA exams are generally performed for three main applications: detection of vascular pathologies, neurosurgery planning, and vascular landmark detection for brain functional analysis. This large field of applications justifies the necessity to provide efficient vessel segmentation tools. Several methods have been proposed during the last fifteen years. However, the obtained results are still not fully satisfying. A solution to improve brain vessel segmentation from MRA data could consist in integrating high-level a priori knowledge in the segmentation process. A preliminary attempt to integrate such knowledge is proposed here. It is composed of two methods devoted to phase contrast MRA (PC MRA) data. The first method is a cerebral vascular atlas creation process, composed of three steps: knowledge extraction, registration, and data fusion. Knowledge extraction is performed using a vessel size determination algorithm based on skeletonization, while a topology preserving non-rigid registration method is used to fuse the information into the atlas. The second method is a segmentation process involving adaptive sets of gray-level hit-or-miss operators. It uses anatomical knowledge modeled by the cerebral vascular atlas to adapt the parameters of these operators (number, size, and orientation) to the searched vascular structures. These two methods have been tested by creating an atlas from a 18 MRA database, and by using it to segment 30 MRA images, comparing the results to those obtained from a region-growing segmentation method.     

An adaptive template-matching method and its application to the boundary detection of brachial artery ultrasound scans

We developed an adaptive template-matching method for vessel wall boundary detection in brachial artery ultrasound (US) scans. The computer-aided identification of lumen-intima and media-adventitia boundaries of the brachial artery US scan is a critical step for flow-mediated vasodilator response measurement, which has become an increasingly important tool in both clinical and research applications. The adaptive template we propose in this paper is a combination of two parameterized Gaussian envelopes that approximates the US pulse envelope. The algorithm for template matching is cast as a constrained nonlinear least squares problem. A best match between the template and the observed US scan line signal results in a set of optimum parameters of the adaptive template, and the location of the boundaries is directly computed from these parameters. We present the results of applying our method to synthetic and clinical data, showing that the adaptive template-matching method provides superior accuracy in detecting the media-adventitia boundaries of both the near wall and the far wall of the vessel to that of conventional edge-detection methods.     

Fetal hydronephrosis and renal artery blood velocity.

The renal artery blood velocity waveform was recorded by Doppler ultrasound in 17 fetuses with hydronephrosis in the third trimester of pregnancy. The waveform was analyzed for pulsatility index and related to the degree of dilatation of the renal pelvis. The pulsatility index was found to be above the renal reference range in only five out of the total of 31 kidneys examined. No relationship was found between the degree of dilatation and pulsatility index. A slight relationship was, however, found between abnormal pulsatility index and the need for operative intervention in the neonatal period. Doppler ultrasound is a valuable tool for evaluating renal circulation, but the results suggest limited clinical value in fetuses with hydronephrosis.     

A simple method for quantification of biotinidase activity in dried blood spot and its application to screening of biotinidase deficiency

A simple and reliable method for quantification of biotinidase (EC.3.5.1.12) activity in dried blood spot was devised by a modification of the colorimetric screening test developed by Heard et al. (1984). The enzyme reaction and hemoglobin denaturation were carried out in a U-bottomed microplate. An aliquot of the reaction solution was transferred to a flat-bottomed microplate. After the coupling reaction was started, the adsorbance was measured in situ by a microplate-reader. Both intra- and inter-assay coefficient of variation (CV) values were less than 10%. Biotinidase activity in dried blood spot showed a good correlation to that in serum (r = 0.912, n = 8). This method was applied in a pilot screening of 18,945 newborns in Sapporo City. No positive results have been obtained as yet.     

反复贴块法培养大鼠主动脉平滑肌细胞

目的：原代培养鼠主动脉平滑肌细胞，传统贴块法往往由于血管片成功贴壁数少而导致失败或存在培养周期长的缺点。反复血管片贴壁法能够克服以上弊端，本实验拟进一步验证。 方法：实验于2007—03/06在南昌大学第二附属医院江西省分子中心重点实验室完成。①实验方法：健康Wistar大鼠2只，断颈法处死，分离胸主动脉，清除结缔组织，纵向剖开血管去除内皮细胞，继续用力刮可见血管片分为两层，去掉外层，剩下即为所需的中膜组织，剪细置于无菌培养瓶底，组织块间距不超过0．5cm，瓶底朝上，向培养瓶内加入5．0～6．0mL含体积分数为0．15胎牛血清的培养液后，放在大平皿上使瓶口稍朝上，置于37℃孵箱，一次性培养瓶放置1h（普通培养瓶2～3h）后将其缓慢翻转平放，使组织块完全浸入培养液中。当一些组织块周围细胞生长相当密集以致失去特有的梭形形态时，即可按1：1或1：2进行传代。②实验评估：采用相差显微镜观察细胞的生长形态及生长规律。免疫化学法检测α-平滑肌肌动蛋白的表达。 结果：①细胞生长形态：原代培养第3天，贴附良好的血管片周围细胞呈辐射状生长，形态多样。4～10d细胞数量增多，细胞生长至融汇后相互平行排列成束或放射状，血管平滑肌细胞特征性“峰”、“谷”状生长特点尤为明显。细胞生长相当密集而传代。②α-平滑肌肌动蛋白免疫组织化学检测：胞浆内出现肌丝，纵向平行排列有密区，α-平滑肌肌动蛋白免疫化学染色呈阳性（棕色）。 结论：利用反复血管片贴壁法成功进行大鼠主动脉平滑肌细胞的原代培养，具有简便易行、细胞损失小、培养周期短等优点。     

Vessel-CAPTCHA: An efficient learning framework for vessel annotation and segmentation

Deep learning techniques for 3D brain vessel image segmentation have not been as successful as in the segmentation of other organs and tissues. This can be explained by two factors. First, deep learning techniques tend to show poor performances at the segmentation of relatively small objects compared to the size of the full image. Second, due to the complexity of vascular trees and the small size of vessels, it is challenging to obtain the amount of annotated training data typically needed by deep learning methods. To address these problems, we propose a novel annotation-efficient deep learning vessel segmentation framework. The framework avoids pixel-wise annotations, only requiring weak patch-level labels to discriminate between vessel and non-vessel 2D patches in the training set, in a setup similar to the CAPTCHAs used to differentiate humans from bots in web applications. The user-provided weak annotations are used for two tasks: (1) to synthesize pixel-wise pseudo-labels for vessels and background in each patch, which are used to train a segmentation network, and (2) to train a classifier network. The classifier network allows to generate additional weak patch labels, further reducing the annotation burden, and it acts as a second opinion for poor quality images. We use this framework for the segmentation of the cerebrovascular tree in Time-of-Flight angiography (TOF) and Susceptibility-Weighted Images (SWI). The results show that the framework achieves state-of-the-art accuracy, while reducing the annotation time by $\sim$77% w.r.t. learning-based segmentation methods using pixel-wise labels for training.     

A case of reocclusion of the renal artery diagnosed by the color Doppler method with evaluation of blood flow direction in the collateral circulation of the kidney in addition to the non-detectable blood signal in the renal artery

A 23-year-old woman was referred to our hospital for an interventional procedure for chronic total occlusion of the right renal artery, probably due to fibromuscular dysplasia (FMD), and for control of renal vascular hypertension. Before percutaneous transluminal renal angioplasty (PTRA), aortography revealed collateral circulation to the right kidney from the lower lumbar artery. After PTRA, however, blood flow in the renal side of the collateral circulation flowed outside from the right renal parenchyma. 4 months later, we could not find a blood flow signal in the right renal artery, and there was a contrary flow signal in the right kidney parenchyma continuously from the extrahilar vessel, possibly a collateral artery. These findings indicated reocclusion of the right artery. We confirmed reocclusion of the renal artery and collateral feeding by contrast dynamic computed tomography (CT), and PTRA was performed again without any complications or reocclusion for 5 months. This is the first case report showing that a back-flowing signal in the right renal parenchyma from the extrahilar artery is useful as an indirect finding suggesting reocclusion.     

Generalized pixel profiling and comparative segmentation with application to arteriovenous malformation segmentation

Extraction of structural and geometric information from 3-D images of blood vessels is a well known and widely addressed segmentation problem. The segmentation of cerebral blood vessels is of great importance in diagnostic and clinical applications, with a special application in diagnostics and surgery on arteriovenous malformations (AVM). However, the techniques addressing the problem of the AVM inner structure segmentation are rare. In this work we present a novel method of pixel profiling with the application to segmentation of the 3-D angiography AVM images. Our algorithm stands out in situations with low resolution images and high variability of pixel intensity. Another advantage of our method is that the parameters are set automatically, which yields little manual user intervention. The results on phantoms and real data demonstrate its effectiveness and potentials for fine delineation of AVM structure.     

A routine assay procedure for monoamine oxidase and its application to human blood platelets

In the radiometric assay procedure for monoamine oxidase separation of the reaction products by ion-exchange column chromatography was optimized. A device was constructed that allowed the separation of 48 samples at the same time. This device can be applied for a great variety of analytical methods. With a 0.1 mM substrate concentration in the incubation mixture, reaction products could be determined with a reproducibility of 2–5%, where the standard deviation depends on the substrate. Using β-phenylethylamine as substrate 20 μg of platelet protein was sufficient for monoamine oxidase activity determinations. The dependence of human blood platelet monoamine oxidase on age and sex were studied using the method.     

A foreign body in the blood vessel: A diagnostic and therapeutic dilemma

Foreign body(FB) in soft tissue is a common injury in trauma, but it is rare for FB to enter the blood vessel. Typical causes of intravascular FB include iatrogenic and non-iatrogenic factors.A 65-year-old Chinese worker's left hand was hit by two colliding metal blocks while operating a machine tool. Then, he referred to our hospital's emergency department of orthopedics. The X-rays showed that metal FB could be seen in trapezium bone regions of the left hand. During the operation, the FB was found in the cephalic vein of his left hand, so the FB was removed by surgery. After six weeks of follow-up, he has returned to normal working conditions.The purpose of this article is to describe the diagnosis and treatment of a rare condition in the emergency department. In our emergency work, it is easy to miss the diagnosis of intravascular FB caused by trauma. To our knowledge, this is the third reported intravascular FB caused by trauma and the first reported intravascular FB was located in the vein of the hand. Detailed medical history and auxiliary examinations are the key to the diagnosis of FB in the blood vessels.     

Shape-based acetabular cartilage segmentation: application to CT and MRI datasets

Purpose

A new method for acetabular cartilage segmentation in both computed tomography (CT) arthrography and magnetic resonance imaging (MRI) datasets with leg tension is developed and tested.

Methods

The new segmentation method is based on the combination of shape and intensity information. Shape information is acquired according to the predictable nonlinear relationship between the U-shaped acetabulum region and acetabular cartilage. Intensity information is obtained from the acetabular cartilage region automatically to complete the segmentation procedures. This method is evaluated using 54 CT arthrography datasets with two different radiation doses and 20 MRI datasets. Additionally, the performance of this method in identifying acetabular cartilage is compared with four other acetabular cartilage segmentation methods.

Results

This method performed better than the comparison methods. Indeed, this method maintained good accuracy level for 74 datasets independent of the cartilage modality and with minimum user interaction in the bone segmentation procedures. In addition, this method was efficient in noisy conditions and in detection of the damaged cartilages with zero thickness, which confirmed its potential clinical usefulness.

Conclusions

Our new method proposes acetabular cartilage segmentation in three different datasets based on the combination of the shape and intensity information. This method executes well in situations where there are clear boundaries between the acetabular and femoral cartilages. However, the acetabular cartilage and pelvic bone information should be obtained from one dataset such as CT arthrography or MRI datasets with leg traction.

     

A review of 3D vessel lumen segmentation techniques: Models,features and extraction schemes

Vascular diseases are among the most important public health problems in developed countries. Given the size and complexity of modern angiographic acquisitions, segmentation is a key step toward the accurate visualization, diagnosis and quantification of vascular pathologies.Despite the tremendous amount of past and on-going dedicated research, vascular segmentation remains a challenging task. In this paper, we review state-of-the-art literature on vascular segmentation, with a particular focus on 3D contrast-enhanced imaging modalities (MRA and CTA). We structure our analysis along three axes: models, features and extraction schemes. We first detail model-based assumptions on the vessel appearance and geometry which can embedded in a segmentation approach. We then review the image features that can be extracted to evaluate these models. Finally, we discuss how existing extraction schemes combine model and feature information to perform the segmentation task.Each component (model, feature and extraction scheme) plays a crucial role toward the efficient, robust and accurate segmentation of vessels of interest. Along each axis of study, we discuss the theoretical and practical properties of recent approaches and highlight the most advanced and promising ones.