We focus on a fundamental task of detecting meaningful line structures, a.k.a., semantic line, in natural scenes. Many previous methods regard this problem as a special case of object detection and adjust existing object detectors for semantic line detection. However, these methods neglect the inherent characteristics of lines, leading to sub-optimal performance. Lines enjoy much simpler geometric property than complex objects and thus can be compactly parameterized by a few arguments. In this paper, we incorporate the classical Hough transform technique into deeply learned representations and propose a one-shot end-to-end learning framework for line detection. By parameterizing lines with slopes and biases, we perform Hough transform to translate deep representations into the parametric domain, in which we perform line detection. Specifically, we aggregate features along candidate lines on the feature map plane and then assign the aggregated features to corresponding locations in the parametric domain. The problem of detecting semantic lines in the spatial domain is transformed into spotting individual points in the parametric domain, making the post-processing steps, i.e., non-maximal suppression, more efficient. Experimental results on our proposed dataset and another public dataset demonstrate the advantages of our method over previous state-of-the-art alternatives.

Deep Hough Transform for Semantic Line Detection.

In this study, a novel targeted MRI contrast agent was developed by coating gadolinium oxide nanoparticles (Gd2O3 NPs) with β-cyclodextrin (CD)-based polyester and targeted by folic acid (FA). The developed Gd2O3@PCD–FA MRI contrast agent was characterized and evaluated in relaxivity, in vitro cell targeting, cell toxicity, blood compatibility and in vivo tumor MR contrast enhancement. In vitro cytotoxicity and hemolysis assays revealed that Gd2O3@PCD–FA NPs have no significant cytotoxicity after 24 and 48 h against normal human breast cell line (MCF-10A) at concentration of up to 50 µg Gd+3/mL and have high blood compatibility at concentration of up to 500 µg Gd+3/mL. In vitro MR imaging experiments showed that Gd2O3@PCD–FA NPs enable targeted contrast T1- and T2-weighted MR imaging of M109 as overexpressing folate receptor cells. Besides, the in vivo analysis indicated that the maximum contrast-to-noise ratio (CNR) of tumor in mice increased after injection of Gd2O3@PCD–FA up to 5.89 ± 1.3 within 1 h under T1-weighted imaging mode and reduced to 1.45 ± 0.44 after 12 h. While CNR increased up to maximum value of 1.98 ± 0.28 after injection of Gd2O3@PCD within 6 h and reduced to 1.12 ± 0.13 within 12 h. The results indicate the potential of Gd2O3@PCD–FA to serve as a novel targeted nano-contrast agent in MRI.

Gadolinium (III) oxide nanoparticles coated with folic acid-functionalized poly(β-cyclodextrin-co-pentetic acid) as a biocompatible targeted nano-contrast agent for cancer diagnostic: in vitro and in vivo studies

Innovation Process in Medical Imaging

Background: Glucose transporter (Glut), a cellular transmembrane receptor, has a key role in the metabolism of cell glucose and is also associated with various human carcinomas.Objective: In this study, we evaluated a magnetic resonance (MR) imaging contrast agent for tumor detection based on paramagnetic gadolinium oxide (Gd2O3) coated polycyclodextrin (PCD) and modified with glucose (Gd2O3@PCD-Glu) for the targeting of overexpressed glucose receptors.Material and Methods: In this experimental study, 3T magnetic resonance imaging (MRI) scanner was used to assess the specific interactions between Glut1-overexpressing tumor cells (MDA-MB-231) and Gd2O3@PCD-Glu NPs. Furthermore, the capacity of transporting Gd2O3@PCD-Glu NPs to tumor cells was evaluated. Results: It was found that the acquired MRI T1 signal intensity of MDA-MB-231 cells that were treated with the Gd2O3@PCD-Glu NPs increased significantly. Based on the results obtained, Gd2O3@PCD-Glu NPs can be applied in targeting Glut1-overexpressing tumor cells in vivo, as well as an MRI-targeted tumor agent to enhance tumor diagnosis. Conclusion: Results have shown that glucose-shell of magnetic nanoparticles has a key role in diagnosing cancer cells of high metabolic activity.

https://jbpe.sums.ac.ir/article_45931_bd0bacd226f6597f8a8c2e8e3753db02.pdf

Glucosamine Conjugated Gadolinium (III) Oxide Nanoparticles as a Novel Targeted Contrast Agent for Cancer Diagnosis in MRI

Computed tomography (CT) images containing metallic objects commonly show severe streaking and shadow artifacts. Metal artifacts are caused by nonlinear beam-hardening effects combined with other factors such as scatter and Poisson noise. In this paper, we propose an implant-specific method that extracts beam-hardening artifacts from CT images without affecting the background image. We found that in cases where metal is inserted in the water (or tissue), the generated beam-hardening artifacts can be approximately extracted by subtracting artifacts generated exclusively by metals. We used a deep learning technique to train nonlinear representations of beam-hardening artifacts arising from metals, which appear as shadows and streaking artifacts. The proposed network is not designed to identify ground-truth CT images (i.e., the CT image before its corruption by metal artifacts). Consequently, these images are not required for training. The proposed method was tested on a dataset consisting of real CT scans of pelvises containing simulated hip prostheses. The results demonstrate that the proposed deep learning method successfully extracts both shadowing and streaking artifacts.

Machine-learning-based nonlinear decomposition of CT images for metal artifact reduction

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Classic Papers in Modern Diagnostic Radiology

[110 years ago: Wilhelm Conrad Roentgen received the first Nobel Prize].

It is 40 years ago that a very popular X-ray device disappeared in German shoe shops: the shoe-fitting fluoroscope or Pedoskop. Since the 1930s, these X-ray machines were an integral part of any good shoe business. Following the entry into force X-Ray Regulation (RoV 1973) the use of these devices was prohibited in Germany.

Strahlenexposition bei Schuhdurchleuchtungsapparaten

Sir Godfrey Hounsfield at 100.

Historical aspects of limiting values for radiation protection

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