UNesT: Local Spatial Representation Learning with Hierarchical Transformer for Efficient Medical Segmentation

Transformer-based models, capable of learning better global dependencies, have recently demonstrated exceptional representation learning capabilities in computer vision and medical image analysis. Transformer reformats the image into separate patches and realizes global communication via the self-attention mechanism. However, positional information between patches is hard to preserve in such 1D sequences, and loss of it can lead to sub-optimal performance when dealing with large amounts of heterogeneous tissues of various sizes in 3D medical image segmentation. Additionally, current methods are not robust and efficient for heavy-duty medical segmentation tasks such as predicting a large number of tissue classes or modeling globally inter-connected tissue structures. To address such challenges and inspired by the nested hierarchical structures in vision transformer, we proposed a novel 3D medical image segmentation method (UNesT), employing a simplified and faster-converging transformer encoder design that achieves local communication among spatially adjacent patch sequences by aggregating them hierarchically. We extensively validate our method on multiple challenging datasets, consisting of multiple modalities, anatomies, and a wide range of tissue classes, including 133 structures in the brain, 14 organs in the abdomen, 4 hierarchical components in the kidneys, inter-connected kidney tumors and brain tumors. We show that UNesT consistently achieves state-of-the-art performance and evaluate its generalizability and data efficiency. Particularly, the model achieves whole brain segmentation task complete ROI with 133 tissue classes in a single network, outperforming prior state-of-the-art method SLANT27 ensembled with 27 networks.Comment: 19 pages, 17 figures. arXiv admin note: text overlap with arXiv:2203.0243

Decoding the dopamine transporter imaging for the differential diagnosis of parkinsonism using deep learning.

PURPOSE This work attempts to decode the discriminative information in dopamine transporter (DAT) imaging using deep learning for the differential diagnosis of parkinsonism. METHODS This study involved 1017 subjects who underwent DAT PET imaging ([11C]CFT) including 43 healthy subjects and 974 parkinsonian patients with idiopathic Parkinson's disease (IPD), multiple system atrophy (MSA) or progressive supranuclear palsy (PSP). We developed a 3D deep convolutional neural network to learn distinguishable DAT features for the differential diagnosis of parkinsonism. A full-gradient saliency map approach was employed to investigate the functional basis related to the decision mechanism of the network. Furthermore, deep-learning-guided radiomics features and quantitative analysis were compared with their conventional counterparts to further interpret the performance of deep learning. RESULTS The proposed network achieved area under the curve of 0.953 (sensitivity 87.7%, specificity 93.2%), 0.948 (sensitivity 93.7%, specificity 97.5%), and 0.900 (sensitivity 81.5%, specificity 93.7%) in the cross-validation, together with sensitivity of 90.7%, 84.1%, 78.6% and specificity of 88.4%, 97.5% 93.3% in the blind test for the differential diagnosis of IPD, MSA and PSP, respectively. The saliency map demonstrated the most contributed areas determining the diagnosis located at parkinsonism-related regions, e.g., putamen, caudate and midbrain. The deep-learning-guided binding ratios showed significant differences among IPD, MSA and PSP groups (P < 0.001), while the conventional putamen and caudate binding ratios had no significant difference between IPD and MSA (P = 0.24 and P = 0.30). Furthermore, compared to conventional radiomics features, there existed average above 78.1% more deep-learning-guided radiomics features that had significant differences among IPD, MSA and PSP. CONCLUSION This study suggested the developed deep neural network can decode in-depth information from DAT and showed potential to assist the differential diagnosis of parkinsonism. The functional regions supporting the diagnosis decision were generally consistent with known parkinsonian pathology but provided more specific guidance for feature selection and quantitative analysis

The abundance and host-seeking behavior of culicine species (Diptera: Culicidae) and Anopheles sinensis in Yongcheng city, people's Republic of China

<p>Abstract</p> <p>Background</p> <p>The knowledge of mosquito species diversity and the level of anthropophily exhibited by each species in a region are of great importance to the integrated vector control. Culicine species are the primary vectors of Japanese encephalitis (JE) virus and filariasis in China. <it>Anopheles sinensis </it>plays a major role in the maintenance of <it>Plasmodium vivax </it>malaria transmission in China. The goal of this study was to compare the abundance and host-seeking behavior of culicine species and <it>An. sinensis </it>in Yongcheng city, a representative region of <it>P. vivax </it>malaria. Specifically, we wished to determine the relative attractiveness of different animal baits versus human bait to culicine species and <it>An. sinensis</it>.</p> <p>Results</p> <p><it>Culex tritaeniorhynchus </it>was the most prevalent mosquito species and <it>An. sinensis </it>was the sole potential vector of <it>P. vivax </it>malaria in Yongcheng city. There were significant differences (P < 0.01) in the abundance of both <it>An. sinensis </it>and <it>Cx. tritaeniorhynchus </it>collected in distinct baited traps. The relative attractiveness of animal versus human bait was similar towards both <it>An. sinensis </it>and <it>Cx. tritaeniorhynchus</it>. The ranking derived from the mean number of mosquitoes per bait indicated that pigs, goats and calves frequently attracted more mosquitoes than the other hosts tested (dogs, humans, and chickens). These trends were similar across all capture nights at three distinct villages. The human blood index (HBI) of female <it>An. sinensis </it>was 2.94% when computed with mixed meals while 3.70% computed with only the single meal. 19:00~21:00 was the primary peak of host-seeking female <it>An. sinensis </it>while 4:00~5:00 was the smaller peak at night. There was significant correlation between the density of female <it>An. sinensis </it>and the average relative humidity (P < 0.05) in Wangshanzhuang village.</p> <p>Conclusions</p> <p>Pigs, goats and calves were more attractive to <it>An. sinensis </it>and <it>Cx. tritaeniorhynchus </it>than dogs, humans, and chickens. Female <it>An. sinensis </it>host-seeking activity mainly occurred from 19:00 to 21:00. Thus, we propose that future vector control against <it>An. sinensis </it>and <it>Cx. tritaeniorhynchus </it>in the areas along the Huang-Huai River of central China should target the interface of human activity with domestic animals and adopt before human hosts go to bed at night.</p

Seismic Performance of SFRC Shear Walls with Window Opening and the Substitution Effect for Steel Bars

Shear walls are important vertical and lateral bearing element in structures. While shear walls with openings are fragile due to stress concentration and the quasi-brittle behavior of concrete in tension. Therefore, additional strengthening rebars are required for the shear walls with openings. However, it aggravates the problem of dense reinforcement which increases the steel cage manufacturing and concrete compaction problem and still lacks countermeasures against concrete damage and cracking. To reduce the rebar demand and improve the damage tolerance of squat reinforced concrete (RC) shear walls with openings, an optimized steel-fiber-reinforced concrete (SFRC) was adopted to understand the seismic performance by cyclical loading test. The tested specimens included a plain RC shear wall without strengthening bar around the opening (for comparison), an SFRC shear wall, and an SFRC shear wall with a reduced distributed steel bar. This paper mainly studies the effect of using SFRC to improve the seismic performance of the open shear wall and to replace the reinforcement around the opening and the shear reinforcement. The hysteresis curves, skeleton curves, stiffness degradation, bearing capacity degradation and energy dissipation of the specimens were analyzed. The results show that the failure can be delayed and relieved, the deformation capacity and energy dissipation can considerably improve, and rebars can be partially replaced by using SFRC

A simplified HTc rf SQUID to analyze the human cardiac magnetic field

We have developed a four-channel high temperature radio-frequency superconducting quantum interference device (HTc rf SQUID) in a simple magnetically shielded room (MSR) that can be used to analyze the cardiac magnetic field. It is more robust and compact than existing systems. To achieve the high-quality magnetocardiographic signal, we explored new adaptive software gradiometry technology constructed by the first-order axial gradiometer with a baseline of 80mm, which can adjust its performance timely with the surrounding conditions. The magnetic field sensitivity of each channel was less than 100fT/√Hz in the white noise region. Especially, in the analysis of MCG signal data, we proposed the total transient mapping (TTM) technique to visualize current density map (CDM), then we focused to observe the time-varying behavior of excitation propagation and estimated the underlying currents at T wave. According to the clear 3D imaging, isomagnetic field and CDM, the position and distribution of a current source in the heart can be visualized. It is believed that our four-channel HTc rf SQUID magnetometer based on biomagnetic system is available to detect MCG signals with sufficient signal-to-noise (SNR) ratio. In addition, the CDM showed the macroscopic current activation pattern, in a way, it has established strong underpinnings for researching the cardiac microscopic movement mechanism and opening the way for its use in clinical diagnosis

A K-SVD Based Compressive Sensing Method for Visual Chaotic Image Encryption

The visually secure image encryption scheme is an effective image encryption method, which embeds an encrypted image into a visual image to realize a secure and secret image transfer. This paper proposes a merging compression and encryption chaos image visual encryption scheme. First, a dictionary matrix D is constructed with the plain image by the K-SVD algorithm, which can encrypt the image while sparsing. Second, an improved Zeraoulia-Sprott chaotic map and logistic map are employed to generate three S-Boxes, which are used to complete scrambling, diffusion, and embedding operations. The secret keys of this scheme contain the initial value of the chaotic system and the dictionary matrix D, which significantly increases the key space, plain image correlation, and system security. Simulation shows the proposed image encryption scheme can resist most attacks and, compared with the existing scheme, the proposed scheme has a larger key space, higher plain image correlation, and better image restoration quality, improving image encryption processing efficiency and security

Suitability Evaluation for Land Reclamation of Nonmetallic Mines in Xinjiang, China

The ecological environment is fragile in Xinjiang, so it is necessary to carry out land reclamation for mines to restore its ecology. The premise of mines land reclamation is to determine the direction of land reclamation, which requires the suitability evaluation for land reclamation. In this paper, the evaluation index system and suitability evaluation model for land reclamation of nonmetallic mines in Xinjiang Uygur Autonomous Region were established. This model was established by using factor analysis, cluster analysis, and discriminant analysis and tested by back-substitution. First, using 149 units of 21 nonmetallic mines as research samples, the samples were divided into 4 categories by a combination of factor and cluster analysis. Then, the samples were trained using a discriminant analysis method to establish the corresponding land reclamation suitability evaluation model. This model was verified by back-substitution with an accuracy of 98.7%, and only 2 of 149 samples were misclassified. Finally, the evaluation model was applied to the Dabancheng Toga Solo limestone mine in Urumqi. Evaluation analysis of 15 land reclamation units of this mine showed satisfactory results. The evaluation model developed here could serve as a powerful complement to the evaluation of land reclamation suitability in Xinjiang

Changes in Particle Size Composition under Seepage Conditions of Reclaimed Soil in Xinjiang, China

The distribution of reclaimed soil particle size under seepage conditions after the management period will directly determine the success or failure of reclamation work. The geotechnical experimental method was used in this paper to study the changes in the granulometric composition of soil. The results show that the granulometric composition of the reclaimed soil varied obviously at different depths. The granulometric composition of the soil at a depth of 10 cm was not much different from undisturbed reclaimed soil (URS). At a depth of 30 cm, as the sharp decrease of the content of fine particles resulted in coarser reclaimed soil, the soil became more uniform, with an increase in porosity and water content. At a depth of 50 cm, the fine particle content was generally slightly lower than that of URS. At a depth of 70 cm, the fine particle content of the soil greatly exceeded that of the URS, with the finest soil particles and lowest porosity. The main reason for the above-mentioned changes of granulometric composition in the reclaimed soil was the seepage in soil caused by irrigation during the management period. The research results can provide a reference for management after land reclamation at non-metallic mines in Xinjiang, China

High-flowable and high-performance steel fiber reinforced concrete adapted by fly ash and silica fume

The incorporation of steel fibers in concrete imparts strain-hardening characteristics, significantly elevating the tensile toughness of the concrete mixture. However, this enhancement often comes at the expense of reduced workability and strength, posing challenges in achieving optimal densification in practical engineering applications. Moreover, the improvement of the performance of steel fiber-reinforced concrete (SFRC) hinges on the establishment of interfacial transition zone (ITZ) between steel fibers and the concrete paste. It has been established that the introduction of fly ash and silica fume to concrete mixtures can increase fluidity and strength. Consequently, this study investigates the impact of fly ash and silica fume on the performance enhancement and workability of SFRC mixtures, scrutinizing both macroscopic and microscopic aspects. Two sets of high-flowable steel fiber-reinforced concretes (HF-SFRC) incorporating silica fume or fly ash were prepared and subjected to testing. The assessment covered mechanical properties, including compressive strength, compressive toughness, and flexural toughness, along with the microstructure. The microstructure provides evidence that fly ash and silica fume reduced the voids in the concrete matrix to different degrees and that the fully hydrated dense matrix contributed to reinforcing the bond between steel fibers and the cement matrix. The synergistic effect among fly ash or silica fume, steel fibers, and cement in the mixture resulted in enhanced flowability and improved mechanical properties in HF-SFRC