Human Treelike Tubular Structure Segmentation: A Comprehensive Review and Future Perspectives

Various structures in human physiology follow a treelike morphology, which often expresses complexity at very fine scales. Examples of such structures are intrathoracic airways, retinal blood vessels, and hepatic blood vessels. Large collections of 2D and 3D images have been made available by medical imaging modalities such as magnetic resonance imaging (MRI), computed tomography (CT), Optical coherence tomography (OCT) and ultrasound in which the spatial arrangement can be observed. Segmentation of these structures in medical imaging is of great importance since the analysis of the structure provides insights into disease diagnosis, treatment planning, and prognosis. Manually labelling extensive data by radiologists is often time-consuming and error-prone. As a result, automated or semi-automated computational models have become a popular research field of medical imaging in the past two decades, and many have been developed to date. In this survey, we aim to provide a comprehensive review of currently publicly available datasets, segmentation algorithms, and evaluation metrics. In addition, current challenges and future research directions are discussed.Comment: 30 pages, 19 figures, submitted to CBM journa

How to Achieve End-to-end Key Distribution for QKD Networks in the Presence of Untrusted Nodes

Quantum key distribution (QKD) networks are expected to enable information-theoretical secure (ITS) communication over a large-scale network. Most researches on relay-based QKD network assume that all relays are completely trustworthy, but the assumption is unrealistic in a complex network. The current study only analyzes the case of passive attacks by untrusted relays (e.g. eavesdropping). However, active attacks by untrusted relays (e.g. spoofing or interfering with the cooperation between honest nodes) are more serious threats and should not be ignored. Taking both passive and active attacks into account, we propose the ITSBFT-QKD networks to defend against untrusted nodes and achieve end-to-end key distribution. In end-to-end key distribution, multiple participating nodes are required to establish trust relationships and cooperate with each other. To prevent attackers from breaking trust relationship and gaining an unreasonable advantage, we incorporate a byzantine consensus scheme to establish and transmit trust relationships in a global QKD network perspective. Moreover, since the security of traditional consensus schemes is lower than the security requirement of QKD networks, we devise a byzantine fault tolerance (BFT) signature scheme to ensure the information-theoretic security of consensus. It provides a new way to construct signature schemes with point-to-point QKD keys in the presence of untrusted relays or nodes. The security of our scheme is analyzed thoroughly from multiple aspects. Our scheme can accommodate up to $MIN\left( C-1,\lfloor \frac{N-1}{3} \rfloor \right)$ untrusted nodes, where $C$ is the node connectivity of the network and $N$ is the number of nodes in the network. Our scheme provides the highest level of security in currently relay-based QKD networks and will significantly promote the application of QKD networks.Comment: 13 pages,7 figure

Large-Kernel Attention for 3D Medical Image Segmentation

Automatic segmentation of multiple organs and tumors from 3D medical images such as magnetic resonance imaging (MRI) and computed tomography (CT) scans using deep learning methods can aid in diagnosing and treating cancer. However, organs often overlap and are complexly connected, characterized by extensive anatomical variation and low contrast. In addition, the diversity of tumor shape, location, and appearance, coupled with the dominance of background voxels, makes accurate 3D medical image segmentation difficult. In this paper, a novel large-kernel (LK) attention module is proposed to address these problems to achieve accurate multi-organ segmentation and tumor segmentation. The advantages of convolution and self-attention are combined in the proposed LK attention module, including local contextual information, long-range dependence, and channel adaptation. The module also decomposes the LK convolution to optimize the computational cost and can be easily incorporated into FCNs such as U-Net. Comprehensive ablation experiments demonstrated the feasibility of convolutional decomposition and explored the most efficient and effective network design. Among them, the best Mid-type LK attention-based U-Net network was evaluated on CT-ORG and BraTS 2020 datasets, achieving state-of-the-art segmentation performance. The performance improvement due to the proposed LK attention module was also statistically validated.Comment: 22 pages, 5 figures, submitted to Cognitive Computatio

On the inverse design of discontinuous abrasive surface to lower friction-induced temperature in grinding: an example of engineered abrasive tools

In order to lower temperature, abrasive tools with passive-grinding, e.g. textured, areas (PGA) have been suggested. However, most of the reported PGA geometries (e.g. slots, holes) have been determined based on the engineering intuition (i.e. trial and error) rather than in-depth phenomenological analysis. To fill this gap, this paper proposes a method to design the PGA geometry according to the desired temperature, i.e. the inverse design method. In the method, the analytical model of grinding temperature for tools with PGA is established and treated as the primary constraint in the inverse problem, while the models of the ground surface roughness and grinding continuity as the subsidiary constraints. The method accuracy is validated by conducting grinding trials with tools with the calculated PGA geometries and comparing their performances (temperature, roughness and force fluctuation) to the required ones. In comparison with conventional tools, our tools designed by the method have been found effective to reduce harmful, or even destructive, thermal effects on the ground surfaces. This work might lay foundation for designing discontinuous abrasive tools, and future work can be probably extended to the tools or the workpiece with more complex shapes (e.g. ball end/cup tools, and free-form workpiece)