Deep learning-based automated scan plane positioning for brain magnetic resonance imaging.

Background: Manual planning of scans in clinical magnetic resonance imaging (MRI) exhibits poor accuracy, lacks consistency, and is time-consuming. Meanwhile, classical automated scan plane positioning methods that rely on certain assumptions are not accurate or stable enough, and are computationally inefficient for practical application scenarios. This study aims to develop and evaluate an effective, reliable, and accurate deep learning-based framework that incorporates prior physical knowledge for automatic head scan plane positioning in MRI. Methods: A deep learning-based end-to-end automated scan plane positioning framework has been developed for MRI head scans. Our model takes a three-dimensional (3D) pre-scan image input, utilizing a cascaded 3D convolutional neural network to detect anatomical landmarks from coarse to fine. And then, with the determined landmarks, accurate scan plane localization can be achieved. A multi-scale spatial information fusion module was employed to aggregate high- and low-resolution features, combined with physically meaningful point regression loss (PRL) function and direction regression loss (DRL) function. Meanwhile, we simulate complex clinical scenarios to design data augmentation strategies. Results: Our proposed approach shows good performance on a clinically wide range of 229 MRI head scans, with a point-to-point absolute error (PAE) of 0.872 mm, a point-to-point relative error (PRE) of 0.10%, and an average angular error (AAE) of 0.502°, 0.381°, and 0.675° for the sagittal, transverse, and coronal planes, respectively. Conclusions: The proposed deep learning-based automated scan plane positioning shows high efficiency, accuracy and robustness when evaluated on varied clinical head MRI scans with differences in positioning, contrast, noise levels and pathologies.

Sanxiapeptin is an ideal preservative with a dual effect of controlling green mold and inducing systemic defense in postharvest citrus.

Green mold is a common postharvest disease infected by Penicillium digitatum that causes citrus fruit decay, and severely affects fruit storage quality. This work aimed to investigate the antifungal activity of Sanxiapeptin against P. digitatum, and elucidate the possible mechanisms involved. Sanxiapeptin was capable of inhibiting spore germination, germ tube length and mycelial growth. The SYTOX green staining assay revealed that Sanxiapeptin targeted the fungal membrane, and changed the membrane permeability, leading to the leakage of cell constituents. Meanwhile, Sanxiapeptin could influence the cell wall permeability and integrity by increasing the activities of chitinase and glucanase, resulting in abnormal chitin consumption and the decrease of glucan. Intriguingly, Sanxiapeptin could effectively control postharvest decay in citrus fruits, and activate the host resistance responses by regulating the phenylpropanoid pathway. In conclusion, Sanxiapeptin exhibits multiphasic antifungal mechanisms of action to control green mold in citrus fruits, shows great potential as novel food preservatives.

Ribosomal Dysfunction Is a Common Pathomechanism in Different Forms of Trichothiodystrophy.

Mutations in a broad variety of genes can provoke the severe childhood disorder trichothiodystrophy (TTD) that is classified as a DNA repair disease or a transcription syndrome of RNA polymerase II. In an attempt to identify the common underlying pathomechanism of TTD we performed a knockout/knockdown of the two unrelated TTD factors TTDN1 and RNF113A and investigated the consequences on ribosomal biogenesis and performance. Interestingly, interference with these TTD factors created a nearly uniform impact on RNA polymerase I transcription with downregulation of UBF, disturbed rRNA processing and reduction of the backbone of the small ribosomal subunit rRNA 18S. This was accompanied by a reduced quality of decoding in protein translation and the accumulation of misfolded and carbonylated proteins, indicating a loss of protein homeostasis (proteostasis). As the loss of proteostasis by the ribosome has been identified in the other forms of TTD, here we postulate that ribosomal dysfunction is a common underlying pathomechanism of TTD.

[A new approach to research graphical performance of MRI RF coil based on the quantitative comparison method].

OBJECTIVE: To compare the performance of three different types of RF coil in 3.0T MRI, the signal-to-noise ratio (SNR) and image uniformity in 3.0 Tesla magnetic resonance imaging system have been studied. MATERIALS AND METHODS: In addition to the measurement of SNR and Uniformity based on the protocol recommend by AAPM, the images had also been analyzed using SPSS and MATLAB to get the SNR distribution along two vertical direction and the whole imaging plane. RESULTS: The SNR with T/R birdcage coil and 8-ch surface coil is seven and twelve times higher than surface coil in the region of interest (ROI), which was set in the center of the phantom images. With regard to the spatial variation of sensitivity, the uniformity of T/R birdcage coil and 8-ch surface coil are also much higher than that of surface coil. CONCLUSION: The images from T/R birdcage and phased array coils are all better than those of surface coil. The SNR of the images from phased array coil is highest while the uniformity of the images from T/R birdcage coil is highest.

[Overview of optimization of MRI RF coil arrays for parallel imaging].

In this paper, an overview is given on the optimization methods of designing RF coil array. Advantages and disadvantages are also discussed.

[2008 Shanghai Customer Satisfaction Survey report of after-sales service for medical imaging equipments].

To improve the after-sales service, a survey aimed at the after-serveis of 3 kinds of medical equipment is applied among 68 hospitals in Shanghai Area in 2008.The Stat. and analysis results are showed in the paper, which will certainly channel off suppliers to set up a harmonious market together.