3D Breast Cancer Segmentation in DCE-MRI Using Deep Learning With Weak Annotation.

Background: Deep learning models require large-scale training to perform confidently, but obtaining annotated datasets in medical imaging is challenging. Weak annotation has emerged as a way to save time and effort.

Purpose: To develop a deep learning model for 3D breast cancer segmentation in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) using weak annotation with reliable performance.

[Applications of Artificial Intelligence in MR Image Acquisition and Reconstruction].

Recently, artificial intelligence (AI) technology has shown potential clinical utility in a wide range of MRI fields. In particular, AI models for improving the efficiency of the image acquisition process and the quality of reconstructed images are being actively developed by the MR research community. AI is expected to further reduce acquisition times in various MRI protocols used in clinical practice when compared to current parallel imaging techniques.

Diagnosis of nasal bone fractures on plain radiographs via convolutional neural networks.

This study aimed to assess the performance of deep learning (DL) algorithms in the diagnosis of nasal bone fractures on radiographs and compare it with that of experienced radiologists. In this retrospective study, 6713 patients whose nasal radiographs were examined for suspected nasal bone fractures between January 2009 and October 2020 were assessed. Our dataset was randomly split into training (n = 4325), validation (n = 481), and internal test (n = 1250) sets; a separate external dataset (n = 102) was used.

χ-Separation Imaging for Diagnosis of Multiple Sclerosis versus Neuromyelitis Optica Spectrum Disorder.

Background Use of χ-separation imaging can provide surrogates for iron and myelin that relate closely to abnormal changes in multiple sclerosis (MS) lesions. Purpose To evaluate the appearances of MS and neuromyelitis optica spectrum disorder (NMOSD) brain lesions on χ-separation maps and explore their diagnostic value in differentiating the two diseases in comparison with previously reported diagnostic criteria. Materials and Methods This prospective study included individuals with MS or NMOSD who underwent χ-separation imaging from October 2017 to October 2020.

[Brain Iron Imaging in Aging and Cognitive Disorders: MRI Approaches].

Iron has a vital role in the human body, including the central nervous system. Increased deposition of iron in the brain has been reported in aging and important neurodegenerative diseases. Owing to the unique magnetic resonance properties of iron, MRI has great potential for assessment of iron deposition, distribution, and non-invasive quantification.

Clinical Implications of Focal Mineral Deposition in the Globus Pallidus on CT and Quantitative Susceptibility Mapping of MRI.

Objective: To assess focal mineral deposition in the globus pallidus (GP) by CT and quantitative susceptibility mapping (QSM) of MRI scans and evaluate its clinical significance, particularly cerebrovascular degeneration.

Materials And Methods: This study included 105 patients (66.1 ± 13.

Multi-Domain Neumann Network with Sensitivity Maps for Parallel MRI Reconstruction.

MRI is an imaging technology that non-invasively obtains high-quality medical images for diagnosis. However, MRI has the major disadvantage of long scan times which cause patient discomfort and image artifacts. As one of the methods for reducing the long scan time of MRI, the parallel MRI method for reconstructing a high-fidelity MR image from under-sampled multi-coil k-space data is widely used.

Fully Automatic Assessment of Background Parenchymal Enhancement on Breast MRI Using Machine-Learning Models.

Background: Automated measurement and classification models with objectivity and reproducibility are required for accurate evaluation of the breast cancer risk of fibroglandular tissue (FGT) and background parenchymal enhancement (BPE).

Purpose: To develop and evaluate a machine-learning algorithm for breast FGT segmentation and BPE classification.

Study Type: Retrospective.

Regulatory T Cells Conditioned Media Stimulates Migration in HaCaT Keratinocytes: Involvement of Wound Healing.

Purpose: Regulatory T (Treg) cells, a type of immune cell, play a very important role in the immune response as a subpopulation of T cells. In this study, we investigated the effects of Treg cells conditioned media (CM) on cell migration. Various cytokines and growth factors of Treg cells CM can effect on re-epithelialization stage during the wound healing.

The complete chloroplast genome of (Ranunculaceae).

The complete chloroplast genome sequence of , a species of the family, was characterized from the assembly of HiSeq (Illumina Co.) paired-end sequencing data. The chloroplast genome of was 155,292 bp in length, with a large single-copy (LSC) region of 84,120 bp, a small single-copy (SSC) region of 18,342 bp, and a pair of identical inverted repeat regions (IRs) of 26,415 bp.

The complete chloroplast genome of (Campanulaceae).

The complete chloroplast genome sequence of was determined by next generation sequencing. The total length of chloroplast genome of was 169,447 bp long, including a large single-copy (LSC) region of 85,253 bp, a small single-copy (SSC) region of 8060 bp, and a pair of identical inverted repeat regions (IRs) of 38,067 bp. A total of 110 genes was annotated, resulting in 79 protein-coding genes, 27 tRNA genes, and 4 rRNA genes.