SWTRU: Star-shaped Window Transformer Reinforced U-Net for medical image segmentation.

In the last decade, deep neural networks have been widely applied to medical image segmentation, achieving good results in computer-aided diagnosis tasks etc. However, the task of segmenting highly complex, low-contrast images of organs and tissues with high accuracy still faces great challenges. To better address this challenge, this paper proposes a novel model SWTRU (Star-shaped Window Transformer Reinforced U-Net) by combining the U-Net network which plays well in the image segmentation field, and the Transformer which possesses a powerful ability to capture global contexts.

Differences in actionable genomic alterations between brain metastases and non‑brain metastases in patients with non‑small cell lung cancer.

Brain metastases (BM) have been closely associated with increased morbidity and poor survival outcomes in patients with non‑small cell lung cancer (NSCLC). Excluding risk factors in histological subtypes, genomic alterations, including epidermal growth factor receptor mutations and anaplastic lymphoma kinase () rearrangements have been also regarded as greater risk factors for BM in the aspect of molecular subtypes. In the present study, 69 tumor tissues and 51 peripheral blood samples from patients with NSCLC were analyzed using a hybridization capture‑based next‑generation sequencing (NGS) panel, including 95 known cancer genes.

EraseNet: End-to-End Text Removal in the Wild.

Scene text removal has attracted increasing research interests owing to its valuable applications in privacy protection, camera-based virtual reality translation, and image editing. However, existing approaches, which fall short on real applications, are mainly because they were evaluated on synthetic or unrepresentative datasets. To fill this gap and facilitate this research direction, this paper proposes a real-world dataset called SCUT-EnsText that consists of 3,562 diverse images selected from public scene text reading benchmarks, and each image is scrupulously annotated to provide visually plausible erasure targets.

HL2 on chromosome 7D of wheat (Triticum aestivum L.) regulates both head length and spikelet number.

A major QTL QSpl.nau-7D, named HL2, was validated for its effects on head length and kernel number per spike using NIL, and mapped to a 0.2 cM interval using recombinants.

TextField: Learning a Deep Direction Field for Irregular Scene Text Detection.

Scene text detection is an important step in the scene text reading system. The main challenges lie in significantly varied sizes and aspect ratios, arbitrary orientations, and shapes. Driven by the recent progress in deep learning, impressive performances have been achieved for multi-oriented text detection.

Association between rs120963, rs152451, rs249935, rs447529, rs8053188, and rs16940342 Polymorphisms in the PALB2 Gene and Breast Cancer Susceptibility: A Meta-Analysis.

Background: The aim of this study was to explore the association between single nucleotide polymorphisms (SNPs) in the rs120963, rs152451, rs249935, rs447529, rs8053188, and rs16940342 loci in the PALB2 gene and breast cancer risk.

Methods: Studies investigating the association between SNPs in the PALB2 gene and breast cancer susceptibility were retrieved from the PubMed, Embase, Web of Science, CNKI (Chinese National Knowledge Infrastructure), WanFang, and CBM (China Biology Medicine) databases. Eligible studies were screened according to inclusion/exclusion criteria and principles of quality evaluation.