Novel anti-VEGFR2 antibody-conjugated nanobubbles for targeted ultrasound molecular imaging in a rabbit VX2 hepatic tumor model.

Nanobubbles (NBs), as ultrasound contrast agents, possess the potential for clinical applications in targeted ultrasound molecular imaging due to their small diameters and the specific molecular markers attached. Previous research studies mainly focused on the tumor-specific recruitment capability or drug carriers based on subcutaneous tumor models. In clinical trials, orthotopic tumor models are considered more clinically relevant and better predictive models for assessing drug efficacy compared to standard subcutaneous models.

Automatic interictal epileptiform discharge (IED) detection based on convolutional neural network (CNN).

Clinical diagnosis of epilepsy significantly relies on identifying interictal epileptiform discharge (IED) in electroencephalogram (EEG). IED is generally interpreted manually, and the related process is very time-consuming. Meanwhile, the process is expert-biased, which can easily lead to missed diagnosis and misdiagnosis.

Temperature sensitive nanogels for real-time imaging during transcatheter arterial embolization.

Several vascular embolization materials are commonly used in clinical practice, however, having application defects of varying degrees, such as poor intraoperative imaging and easy recanalization of embolized blood vessels, they are challenging for application during Transcatheter arterial embolization (TAE). Thus, an intraoperative visible vascular embolization material with good embolization effect and biocompatibility can improve transcatheter arterial embolization clinical efficacy to some extent. Our study aimed to synthesize a novel vascular embolization material that can achieve complete embolization of arterial trunks and peripheral vessels, namely poly (N-isopropyl acrylamide)--acrylic acid nanogel (NIPAM--AA).

A thermosensitive Pickering gel emulsion with a high oil-water ratio for long-term X-ray imaging and permanent embolization of arteries.

Iodized oil has an excellent X-ray imaging effect, but it shows poor embolization performance. When used as an embolic agent, it is easily washed off by the blood flow and eliminated from the body. Therefore, it is essential to use iodized oil in combination with solid embolic agents such as gelatin sponge or to perform multiple embolization procedures to achieve the therapeutic effect.

Synthesis of Prostate MR Images for Classification Using Capsule Network-Based GAN Model.

Prostate cancer remains a major health concern among elderly men. Deep learning is a state-of-the-art technique for MR image-based prostate cancer diagnosis, but one of major bottlenecks is the severe lack of annotated MR images. The traditional and Generative Adversarial Network (GAN)-based data augmentation methods cannot ensure the quality and the diversity of generated training samples.

Laplacian Eigenmaps Network-Based Nonlocal Means Method for MR Image Denoising.

Magnetic resonance (MR) images are often corrupted by Rician noise which degrades the accuracy of image-based diagnosis tasks. The nonlocal means (NLM) method is a representative filter in denoising MR images due to its competitive denoising performance. However, the existing NLM methods usually exploit the gray-level information or hand-crafted features to evaluate the similarity between image patches, which is disadvantageous for preserving the image details while smoothing out noise.

PCANet based nonlocal means method for speckle noise removal in ultrasound images.

Speckle reduction remains a critical issue for ultrasound image processing and analysis. The nonlocal means (NLM) filter has recently attached much attention due to its competitive despeckling performance. However, the existing NLM methods usually determine the similarity between two patches by directly utilizing the gray-level information of the noisy image, which renders it difficult to represent the structural similarity of ultrasound images effectively.