Histogram of Oriented Gradients meet deep learning: A novel multi-task deep network for 2D surgical image semantic segmentation

We present our novel deep multi-task learning method for medical image segmentation. Existing multi-task methods demand ground truth annotations for both the primary and auxiliary tasks. Contrary to it, we propose to generate the pseudo-labels of an auxiliary task in an unsupervised manner. To generate the pseudo-labels, we leverage Histogram of Oriented Gradients (HOGs), one of the most widely used and powerful hand-crafted features for detection. Together with the ground truth semantic segmentation masks for the primary task and pseudo-labels for the auxiliary task, we learn the parameters of the deep network to minimize the loss of both the primary task and the auxiliary task jointly. We employed our method on two powerful and widely used semantic segmentation networks: UNet and U2Net to train in a multi-task setup. To validate our hypothesis, we performed experiments on two different medical image segmentation data sets. From the extensive quantitative and qualitative results, we observe that our method consistently improves the performance compared to the counter-part method. Moreover, our method is the winner of FetReg Endovis Sub-challenge on Semantic Segmentation organised in conjunction with MICCAI 2021. Code and implementation details are available at:https://github.com/thetna/medical_image_segmentation.     

Contour-aware network with class-wise convolutions for 3D abdominal multi-organ segmentation

Accurate delineation of multiple organs is a critical process for various medical procedures, which could be operator-dependent and time-consuming. Existing organ segmentation methods, which were mainly inspired by natural image analysis techniques, might not fully exploit the traits of the multi-organ segmentation task and could not accurately segment the organs with various shapes and sizes simultaneously. In this work, the characteristics of multi-organ segmentation are considered: the global count, position and scale of organs are generally predictable, while their local shape and appearance are volatile. Thus, we supplement the region segmentation backbone with a contour localization task to increase the certainty along delicate boundaries. Meantime, each organ has exclusive anatomical traits, which motivates us to deal with class variability with class-wise convolutions to highlight organ-specific features and suppress irrelevant responses at different field-of-views.To validate our method with adequate amounts of patients and organs, we constructed a multi-center dataset, which contains 110 3D CT scans with 24,528 axial slices, and provided voxel-level manual segmentations of 14 abdominal organs, which adds up to 1,532 3D structures in total. Extensive ablation and visualization studies on it validate the effectiveness of the proposed method. Quantitative analysis shows that we achieve state-of-the-art performance for most abdominal organs, and obtain 3.63 mm 95% Hausdorff Distance and 83.32% Dice Similarity Coefficient on an average.     

经桡动脉途径介入治疗冠状动脉钙化病变的临床应用

目的探讨经桡动脉途径行冠状动脉介入性治疗冠状动脉钙化临床应用。方法总结2008年4月至2009年12月我科应用经桡动脉途径行冠状动脉介入性治疗冠状动脉钙化病例182例临床资料。结果介入治疗成功177例,成功率为97．25％;介入治疗不成功5例,所用病例出院时桡动脉搏动良好,手部无缺血。术后3个月随访发现挠动脉搏动明显减弱或消失,但无手部缺血或功能障碍。结论经桡动脉途径行冠状动脉介入性治疗冠状动脉钙化具有创伤小、易于压迫和止血、局部出血和血管并发症少、无需卧床、不会伤及手腕神经,不影响手腕的功能;不影响抗凝药物的持续使用。住院时间缩短、减少住院费用等优点。     

冠状动脉旁路移植术96例治疗总结

目的：总结应用冠状动脉旁路移植术(CABG)治疗冠心病(CAD)的早期效果和经验。方法：回顾性分析96例CABG。应用体外循环(CPB)74例，非体外循环22例。搭桥数264支。平均2．7支。对手术方法、主要并发症和术后处理进行分析总结。结果：本组96例手术，95例患者均痊愈出院，1例死于顽固性快速室上性心律失常伴室性心律失常。术后发生心律失常16例；气胸1例，为呼吸机辅助下自发性气胸；心功能不全32例；二次开胸止血1例；切口感染2例；42例取静脉侧下肢有轻度水肿，2～4个月后消失；胸腔积液11例。上述并发症均给予相应处理后痊愈。术后心绞痛症状消失者61例，明显减轻者29例。无明显改善者6例。92例随访1～41个月，随访率96．8％，所有患者心功能均得到明显改善。结论：合理的选择病人，成熟的手术技术，良好的心肌保护及加强术后管理，能有效提高冠状动脉旁路移植术的疗效。     

非体外循环下冠状动脉搭桥术在高危老年冠心病患者中的应用

目的总结非体外循环下冠状动脉搭桥术(OPCABG)在高危老年冠心病患者中的应用经验。方法 2005年1月至2009年12月对23例高危老年冠心病患者行OPCABG治疗。手术在常温全麻下进行,采用前胸正中切口显露心脏。2例直接采用大隐静脉(SV)行SV-左前降支(LAD)搭桥;9例取乳内动脉(IMA)和SV,行IMA-LAD、升主动脉-SV序贯搭桥;12例取IMA和SV,行IMA-LAD、升主动脉-IMA搭桥。结果全组手术均顺利完成,无转体外循环完成手术者;总共搭桥74条,平均每例搭桥3.1条;早期死亡1例,出现呼吸衰竭1例,急性左心衰1例,术后出血二次开胸手术2例,胸骨感染1例;术后心绞痛完全缓解20例,明显缓解2例。结论高危老年患者行OPCABG是一种安全、有效的方法 ,特别对一些不能耐受体外循环的患者是一种可行的方法 。     

Grayscale self-adjusting network with weak feature enhancement for 3D lumbar anatomy segmentation

The automatic segmentation of lumbar anatomy is a fundamental problem for the diagnosis and treatment of lumbar disease. The recent development of deep learning techniques has led to remarkable progress in this task, including the possible segmentation of nerve roots, intervertebral discs, and dural sac in a single step. Despite these advances, lumbar anatomy segmentation remains a challenging problem due to the weak contrast and noise of input images, as well as the variability of intensities and size in lumbar structures across different subjects. To overcome these challenges, we propose a coarse-to-fine deep neural network framework for lumbar anatomy segmentation, which obtains a more accurate segmentation using two strategies. First, a progressive refinement process is employed to correct low-confidence regions by enhancing the feature representation in these regions. Second, a grayscale self-adjusting network (GSA-Net) is proposed to optimize the distribution of intensities dynamically. Experiments on datasets comprised of 3D computed tomography (CT) and magnetic resonance (MR) images show the advantage of our method over current segmentation approaches and its potential for diagnosing and lumbar disease treatment.     

亚秒螺旋CT三维重建与冠脉造影对冠脉病变的对比研究

目的研究双螺旋CT(DHCT)亚秒扫描与三维重建CT血管造影(CTA)技术对于冠脉病变的检测能力,探讨其诊断冠脉病变的敏感性及特异性,并对影响成像因素进行探讨。方法随机选择临床疑诊冠心病而行亚秒双螺旋CT(DHCT)和冠状动脉造影(CAG)检查患者共54例,分为冠心病组和正常对照组,其中CAG确诊为冠心病35例,CAG与CT检查时间相隔1～7d,DHCT检查分为2个步骤,先平扫,检测冠脉钙化并计积分,然后增强扫描行冠状动脉CT血管成像。结果①DHCT平扫检测冠脉钙化,CAG显示有意义狭窄组钙化积分217±395分,正常组钙化积分28±84分,两组差异明显(P<0.001)。②以冠状动脉造影(CAG)结果为金标准,DHCT显示冠脉病变诊断敏感性60%,特异性63%,准确性64%。结论DHCT可作为冠心病高危人群的一种筛查手段,对于冠状动脉近中段高度和完全性梗阻病变有较高的诊断价值。     

重症冠心病非体外循环冠状动脉搭桥术

目的 总结21例重症冠心病非体外循环冠状动脉搭桥手术的临床体会。方法 先行乳内动脉与前降支的吻合，或在主动脉内球囊反搏支持下完成手术。结果 平均手术时间216（196-286）分钟，3例搭桥3根，15例搭桥4根，3例搭桥5根（4根/人），平均术后呼吸机辅助时间6（3-8）小时，术后应用多巴胺和多巴酚丁胺进行循环功能支持者14例，应用主动脉内球囊反搏2例，均于术后48小时内撤除，术后早期发生房颤，房扑伴阵发性室上速者12例，频发室性早搏者3例，心包填塞二次开胸止血者2例，结论 重症冠心病非体外循环冠状动脉搭桥手术，应充分进行术前准备，制订合理的麻醉和手术方案。加强术中密切配合，重视全面的术后处理。     

老年冠心病人甘油三脂与冠状动脉病变的相关分析

目的 探讨老年冠心病人（CHD）血清甘油三酯（TG）对冠状动脉病变的影响。方法 对不吸烟，无合并高血压、糖尿病的老年CHD病人的血脂进行测定，把血脂正常者45例和单纯TG增高（HTG）72例分为两组：与冠状动脉造影（CAG）阳性结果进行比较。结果 冠状动脉三支病变在HTG组占38．9％，血脂正常组占15．6％（P＜0．05）；冠状动脉狭窄程度≥90％在HTG组占56．3％，血脂正常组占20．2（P＜0．001）。结论 老年CHD病人单纯TG增高的冠状动脉病变较血脂正常者累及血管支数多、狭窄程度严重。     

Automatic segmentation of 3D micro-CT coronary vascular images

Although there are many algorithms available in the literature aimed at segmentation and model reconstruction of 3D angiographic images, many are focused on characterizing only a part of the vascular network. This study is motivated by the recent emerging prospects of whole-organ simulations in coronary hemodynamics, autoregulation and tissue oxygen delivery for which anatomically accurate vascular meshes of extended scale are highly desirable. The key requirements of a reconstruction technique for this purpose are automation of processing and sub-voxel accuracy. We have designed a vascular reconstruction algorithm which satisfies these two criteria. It combines automatic seeding and tracking of vessels with radius detection based on active contours. The method was first examined through a series of tests on synthetic data, for accuracy in reproduced topology and morphology of the network and was shown to exhibit errors of less than 0.5 voxel for centerline and radius detections, and 3 degrees for initial seed directions. The algorithm was then applied on real-world data of full rat coronary structure acquired using a micro-CT scanner at 20 microm voxel size. For this, a further validation of radius quantification was carried out against a partially rescanned portion of the network at 8 microm voxel size, which estimated less than 10% radius error in vessels larger than 2 voxels in radius.     

Accuracy and rate of coronary artery segment visualization with CT angiography for the non-invasive detection of coronary artery stenoses

Objectives To evaluate CT coronary angiography (CTA) when compared with catheter coronary angiography (CCA), for the detection of coronary artery stenoses and rate of optimal coronary artery segment visualization. Method Retrospective, two-center study enrolling 26 patients who underwent CCA and ECG-gated 16-detector CTA (slice thickness 0.6 mm; rotation 500 ms). Results and conclusion 283 segments were available for postprocessing. Sensitivity, specificity, and positive predictive value were, respectively, 80, 100, and 100%, for detecting more than 50% luminal stenoses, when optimally visualized segments were considered, in comparison to CCA. Negative predictive value was excellent (98%). Rate of non-optimally visualized coronary segments was 26%. Most clinical benefits of coronary CT angiography should probably be obtained when it is performed to exclude significant stenoses on selected populations of patients with a low pre-test probability of severe coronary artery disease, and under optimal conditions of controlled heart rate and minimal presence of calcium.     

Transformer guided progressive fusion network for 3D pancreas and pancreatic mass segmentation

Pancreatic masses are diverse in type, often making their clinical management challenging. This study aims to address the task of various types of pancreatic mass segmentation and detection while accurately segmenting the pancreas. Although convolution operation performs well at extracting local details, it experiences difficulty capturing global representations. To alleviate this limitation, we propose a transformer guided progressive fusion network (TGPFN) that utilizes the global representation captured by the transformer to supplement long-range dependencies lost by convolution operations at different resolutions. TGPFN is built on a branch-integrated network structure, where the convolutional neural network and transformer branches first perform separate feature extraction in the encoder, and then the local and global features are progressively fused in the decoder. To effectively integrate the information of the two branches, we design a transformer guidance flow to ensure feature consistency, and present a cross-network attention module to capture the channel dependencies. Extensive experiments with nnUNet (3D) show that TGPFN improves the mass segmentation (Dice: 73.93% vs. 69.40%) and detection accuracy (detection rate: 91.71% vs. 84.97%) on 416 private CTs, and also obtains performance improvements of mass segmentation (Dice: 43.86% vs. 42.07%) and detection (detection rate: 83.33% vs. 71.74%) on 419 public CTs.     

Image guidance for coronary artery bypass grafting

Objective  Open heart bypass graft surgery is the standard treatment for advanced cases of coronary heart disease. Optimal placement of the bypass graft anastomosis is very important for the success of the procedure. Therefore, detailed and precise knowledge about the path and morphology of the target vessel is crucial for the operating surgeon. Materials and methods  To provide such information during the procedure, a novel surgical assistance system for open heart bypass graft surgery was designed which merges preoperative maps of the coronary arteries with intraoperative data. The patient-specific vessel map was generated from multi-slice computed tomography (MSCT), while the intraoperative data were obtained using a stereo camera system. A registration approach based on mutually shared anatomical landmarks on the heart surface was employed. Results  Successful registration of MSCT and stereo video data was performed for five patients, demonstrating that 2D–2D and 3D–3D Procrustes registration could produce mean accuracies between 2 and 5 mm. Conclusion  The target vessel visualization and registration approach presented in this work is feasible and can produce accuracies sufficient to justify future in vivo intraoperative testing.     

双源CT冠状动脉血管成像对冠状动脉狭窄的诊断价值分析

目的:探讨应用双源CT冠状动脉血管成像(DSCT-CA)的检查方式对诊断冠状动脉狭窄的价值.方法:选取2019年1月—2020年5月期间我院65例疑似冠状动脉狭窄的患者,均接受冠脉造影(CAG)与DSCT-CA检查,以CAG检查为金标准,评价DSCT-CA对狭窄情况的诊断价值,并且以冠状动脉狭窄50％为界限,分析DSC...     

实时三维彩色超声心动图诊断冠状动脉瘘的价值

目的：探讨实时三维彩色超声心动图在诊断冠状动脉瘘中的价值。方法：对15例先天性冠状动脉瘘患者行实时三维彩色超声心动图检查，实时立体显示扩张的冠状动脉并仔细追踪，寻找其在心腔的瘘口。结果：15例冠状动脉瘘中，右冠状动脉瘘6例，左冠状动脉瘘9例。二维超声和实时三维彩色超声心动图估测瘘口的最大径与造影估测大小的相关性分别为r=0．95，P〈0．05及r=0．99，P〈0．05。实时三维彩色超声心动图真实精确地显示了显著扩张的冠状动脉，以及瘘口处血流起源、方向和立体空间分布。结论：实时三维彩色超声心动图对冠状动脉瘘的诊断、治疗效果的评价有重要的临床价值。     

多巴酚丁胺负荷超声心动图对冠心病诊断价值的研究

对43例冠心病(CAD)患者和31例健康人进行了多巴酚丁胺负荷超声心动图(DSE)检查,其诊断CAD的敏感性为90.7%,特异性为100%;与运动超声心动图(ES—2DE)相近,此法简便、安全、克服了ES—2DE的缺陷和应用限制.     

Ms RED: A novel multi-scale residual encoding and decoding network for skin lesion segmentation

Computer-Aided Diagnosis (CAD) for dermatological diseases offers one of the most notable showcases where deep learning technologies display their impressive performance in acquiring and surpassing human experts. In such the CAD process, a critical step is concerned with segmenting skin lesions from dermoscopic images. Despite remarkable successes attained by recent deep learning efforts, much improvement is still anticipated to tackle challenging cases, e.g., segmenting lesions that are irregularly shaped, bearing low contrast, or possessing blurry boundaries. To address such inadequacies, this study proposes a novel Multi-scale Residual Encoding and Decoding network (Ms RED) for skin lesion segmentation, which is able to accurately and reliably segment a variety of lesions with efficiency. Specifically, a multi-scale residual encoding fusion module (MsR-EFM) is employed in an encoder, and a multi-scale residual decoding fusion module (MsR-DFM) is applied in a decoder to fuse multi-scale features adaptively. In addition, to enhance the representation learning capability of the newly proposed pipeline, we propose a novel multi-resolution, multi-channel feature fusion module (M²F²), which replaces conventional convolutional layers in encoder and decoder networks. Furthermore, we introduce a novel pooling module (Soft-pool) to medical image segmentation for the first time, retaining more helpful information when down-sampling and getting better segmentation performance. To validate the effectiveness and advantages of the proposed network, we compare it with several state-of-the-art methods on ISIC 2016, 2017, 2018, and PH². Experimental results consistently demonstrate that the proposed Ms RED attains significantly superior segmentation performance across five popularly used evaluation criteria. Last but not least, the new model utilizes much fewer model parameters than its peer approaches, leading to a greatly reduced number of labeled samples required for model training, which in turn produces a substantially faster converging training process than its peers. The source code is available at https://github.com/duweidai/Ms-RED.     

Congenital absence of the right coronary artery: A case report

BACKGROUNDAs a rare anomaly, congenital absence of the right coronary artery (RCA) occurs during the development of coronary artery. Patients with congenital absence of the RCA often show no clinical symptoms, and this disease is considered benign. The left coronary artery gives blood supply to the whole myocardium. The prevalence of congenital absence of the RCA is approximately 0.024%-0.066%. There are few cases reported as for this disease. In this work, a patient, with congenital absence of the RCA diagnosed by coronary angiography (CAG), was described. CASE SUMMARYA 41-year-old man arrived at our hospital for treatment, due to the repeated palpitations for a duration of one year. Considering the possibility of coronary heart disease, the patient underwent CAG that indicated the congenital absence of the RCA. Unfortunately, the patient refused to accept computed tomography coronary angiography (CTCA), to further confirm the congenital absence of the RCA.CONCLUSIONSingle coronary artery is a rare type of coronary artery abnormality, which usually has no obvious clinical manifestations and is considered as a benign disease. CAG is the main means by which congenital absence of the RCA can be diagnosed, and the disease can also be further confirmed by CTCA.