Structure boundary-preserving U-Net for prostate ultrasound image segmentation

Prostate cancer diagnosis is performed under ultrasound-guided puncture for pathological cell extraction. However, determining accurate prostate location remains a challenge from two aspects: (1) prostate boundary in ultrasound images is always ambiguous; (2) the delineation of radiologists always occupies multiple pixels, leading to many disturbing points around the actual contour. We proposed a boundary structure-preserving U-Net (BSP U-Net) in this paper to achieve precise prostate contour. BSP U-Net incorporates prostate shape prior to traditional U-Net. The prior shape is built by the key point selection module, which is an active shape model-based method. Then, the module plugs into the traditional U-Net structure network to achieve prostate segmentation. The experiments were conducted on two datasets: PH2 + ISBI 2016 challenge and our private prostate ultrasound dataset. The results on PH2 + ISBI 2016 challenge achieved a Dice similarity coefficient (DSC) of 95.94% and a Jaccard coefficient (JC) of 88.58%. The results of prostate contour based on our method achieved a higher pixel accuracy of 97.05%, a mean intersection over union of 93.65%, a DSC of 92.54%, and a JC of 93.16%. The experimental results show that the proposed BSP U-Net has good performance on PH2 + ISBI 2016 challenge and prostate ultrasound image segmentation and outperforms other state-of-the-art methods

Geographical Variations in the Environmental Determinants of Physical Inactivity among U.S. Adults

Physical inactivity is a major modifiable risk factor for morbidity, disability and premature mortality worldwide. This study assessed the geographical variations in the impact of environmental quality on physical inactivity among U.S. adults. Data on county-level prevalence of leisure-time physical inactivity came from the Behavioral Risk Factor Surveillance System. County environment was measured by the Environmental Quality Index (EQI), a comprehensive index of environmental conditions that affect human health. The overall EQI consists of five subdomains—air, water, land, social, and built environment. Geographically weighted regressions (GWRs) were performed to estimate and map county-specific impact of overall EQI and its five subdomains on physical inactivity prevalence. The prevalence of leisure-time physical inactivity among U.S. counties was 25% in 2005. On average, one standard deviation decrease in the overall EQI was associated with an increase in county-level prevalence of leisure-time physical inactivity by nearly 1%. However, substantial geographical variations in the estimated environmental determinants of physical inactivity were present. The estimated changes of county-level prevalence of leisure-time physical inactivity resulted from one standard deviation decrease of the overall EQI ranged from an increase of over 3% to a decrease of nearly 2% across U.S. counties. Analogous, the estimated changes of county-level prevalence of leisure-time physical inactivity resulted from one standard deviation decrease of the EQI air, water, land, social, and built environment subdomains ranged from an increase of 2.6%, 1.5%, 2.9%, 3.3%, and 1.7% to a decrease of 2.9%, 1.4%, 2.4%, 2.4%, and 0.8% across U.S. counties, respectively. Given the substantial heterogeneities in the environmental determinants of physical inactivity, locally customized physical activity interventions are warranted to address the most concerning area-specific environmental issue

Effects of early standardized management on the growth trajectory of offspring with gestational diabetes mellitus at 0–5 years old: a preliminary longitudinal study

Abstract To explore the application value of early standardized management in the delivery of neonates of pregnant women with gestational diabetes mellitus (GDM). Parturient diagnosed with GDM and their offspring were selected in our hospital from January 1, 2015 to December 31, 2017 to underwent early standardized management. Non-GDM pregnant women and their offspring were selected as the control group. The growth and development of children aged 0–5 years in the two groups were longitudinally followed up, and the mixed linear model was used to evaluate and compare the growth trajectories. There was no significant difference in height and weight between the two groups at 1 year old (P > 0.05), but the BMI of the GDM group was significantly higher than that in the control group. After 1 year of age, both groups of offspring were similar in height, weight, and BMI, and these similarities persisted at 2, 3, 4, and 5 years of age. After controlling for covariates, the weight, length/height of the two groups of children were slightly different in the growth trajectories between 0–1 years old, 1–2 years old, 2–3 years old, 3–4 years old, and 4–5 years old with no statistical significance (P > 0.05). Although growth differences between the two groups of children were detected within 1 year of age, there were no significant differences in growth trajectories from 1 to 5 years between two groups, which proved that early standardized management has positive significance

QTL Analysis of Spike Morphological Traits and Plant Height in Winter Wheat (Triticum aestivum L.) Using a High-Density SNP and SSR-Based Linkage Map

Wheat yield can be enhanced by modifying the spike morphology and the plant height. In this study, a population of 191 F9 recombinant inbred lines (RILs) was developed from a cross between two winter cultivars Yumai 8679 and Jing 411. A dense genetic linkage map with 10,816 markers was constructed by incorporating single nucleotide polymorphism (SNP) and simple sequence repeat (SSR) marker information. Five spike morphological traits and plant height were evaluated under nine environments for the RILs and parental lines, and the number of detected environmentally stable QTLs were 18 and 3, respectively. The 1RS/1BL (rye) translocation increased both spike length and spikelet number with constant spikelet compactness. The QPht.cau-2D.1 was identical to gene Rht8, which decreased spike length without modifying spikelet number. Notably, four novel QTLs locating on chromosomes 1AS (QSc.cau-1A.1), 2DS (QSc.cau-2D.1) and 7BS (QSl.cau-7B.1 and QSl.cau-7B.2) were firstly identified in this study, which provide further insights into the genetic factors that shaped the spike morphology in wheat. Moreover, SNP markers tightly linked to previously reported QTLs will eventually facilitate future studies including their positional cloning or marker-assisted selection

BPAT-UNet: Boundary preserving assembled transformer UNet for ultrasound thyroid nodule segmentation

International audienceBACKGROUND AND OBJECTIVE: Accurate and efficient segmentation of thyroid nodules on ultrasound images is critical for computer-aided nodule diagnosis and treatment. For ultrasound images, Convolutional neural networks (CNNs) and Transformers, which are widely used in natural images, cannot obtain satisfactory segmentation results, because they either cannot obtain precise boundaries or segment small objects. METHODS: To address these issues, we propose a novel Boundary-preserving assembly Transformer UNet (BPAT-UNet) for ultrasound thyroid nodule segmentation. In the proposed network, a Boundary point supervision module (BPSM), which adopts two novel self-attention pooling approaches, is designed to enhance boundary features and generate ideal boundary points through a novel method. Meanwhile, an Adaptive multi-scale feature fusion module (AMFFM) is constructed to fuse features and channel information at different scales. Finally, to fully integrate the characteristics of high-frequency local and low-frequency global, the Assembled transformer module (ATM) is placed at the bottleneck of the network. The correlation between deformable features and features-among computation is characterized by introducing them into the above two modules of AMFFM and ATM. As the design goal and eventually demonstrated, BPSM and ATM promote the proposed BPAT-UNet to further constrain boundaries, whereas AMFFM assists to detect small objects. RESULTS: Compared to other classical segmentation networks, the proposed BPAT-UNet displays superior segmentation performance in visualization results and evaluation metrics. Significant improvement of segmentation accuracy was shown on the public thyroid dataset of TN3k with Dice similarity coefficient (DSC) of 81.64% and 95th percentage of the asymmetric Hausdorff distance (HD95) of 14.06, whereas those on our private dataset were with DSC of 85.63% and HD95 of 14.53, respectively. CONCLUSIONS: This paper presents a method for thyroid ultrasound image segmentation, which achieves high accuracy and meets the clinical requirements. Code is available at https://github.com/ccjcv/BPAT-UNet