Magnetic resonance imaging-based deep learning imaging biomarker for predicting functional outcomes after acute ischemic stroke.

Purpose: Clinical risk scores are essential for predicting outcomes in stroke patients. The advancements in deep learning (DL) techniques provide opportunities to develop prediction applications using magnetic resonance (MR) images. We aimed to develop an MR-based DL imaging biomarker for predicting outcomes in acute ischemic stroke (AIS) and evaluate its additional benefit to current risk scores.

InertialNet: Inertial Measurement Learning for Simultaneous Localization and Mapping.

SLAM (simultaneous localization and mapping) plays a crucial role in autonomous robot navigation. A challenging aspect of visual SLAM systems is determining the 3D camera orientation of the motion trajectory. In this paper, we introduce an end-to-end network structure, InertialNet, which establishes the correlation between the image sequence and the IMU signals.

Diagnosis of Polypoidal Choroidal Vasculopathy From Fluorescein Angiography Using Deep Learning.

Purpose: To differentiate polypoidal choroidal vasculopathy (PCV) from choroidal neovascularization (CNV) and to determine the extent of PCV from fluorescein angiography (FA) using attention-based deep learning networks.

Methods: We build two deep learning networks for diagnosis of PCV using FA, one for detection and one for segmentation. Attention-gated convolutional neural network (AG-CNN) differentiates PCV from other types of wet age-related macular degeneration.

Hyaluronic acid on the urokinase sustained release with a hydrogel system composed of poloxamer 407: HA/P407 hydrogel system for drug delivery.

Pleural empyema is an inflammatory condition characterized by accumulation of pus inside the pleural cavity, which is usually followed by bacterial pneumonia. During the disease process, the pro-inflammatory and pro-fibrotic cytokines in the purulent pleural effusion cause proliferation of fibroblasts and deposition of extracellular matrix, which lead to fibrin deposition and fibrothorax. Urokinase instillation therapy through a chest drainage tube is frequently used for fibrinolysis in patients with empyema.

Buyang Huanwu Tang inhibits cellular epithelial-to-mesenchymal transition by inhibiting TGF-β1 activation of PI3K/Akt signaling pathway in pulmonary fibrosis model in vitro.

Background: Pulmonary fibrosis (PF) is a chronic and progressive interstitial lung disease. Buyang Huanwu Tang (BYHWT), a classical traditional Chinese medicine formula, has been widely utilized for the treatment of PF in China. This present study aimed to explore the mechanism of BYHWT in the treatment of PF in vitro.

Buyang Huanwu Decoction Ameliorates Bleomycin-Induced Pulmonary Fibrosis in Rats via Downregulation of Related Protein and Gene Expression.

Little is known about the effects of Buyang Huanwu decoction on pulmonary fibrosis. Herein, 144 healthy SD rats were randomly divided into six groups: blank control group (B), model control group (M), positive medicine control group (Mp), and high-, moderate-, and low-dose Buyang Huanwu decoction groups (Hd, Md, and Ld). A pulmonary fibrosis model was established by endotracheal injection of bleomycin.

Accurate Joint-Alignment of Indocyanine Green and Fluorescein Angiograph Sequences for Treatment of Subretinal Lesions.

In ophthalmology, aligning images in indocyanine green and fluorescein angiograph sequences is important for the treatment of subretinal lesions. This paper introduces an algorithm that is tailored to align jointly in a common reference space all the images in an angiogram sequence containing both modalities. To overcome the issues of low image contrast and low signal-to-noise ratio for late-phase images, the structural similarity between two images is enhanced using Gabor wavelet transform.

Temporally Coherent Illumination Normalization for Indocyanine Green Video Angiography.

Indocyanine green (ICG) angiography is an imaging method for doctors to observe choroidal abnormalities in human eyes. The ICG angiograms typically exhibit inhomogeneous illumination, which poses serious difficulties for the development of computer-aided diagnostic tools. In this paper, we propose a novel illumination normalization method to alleviate the inhomogeneous illumination in ICG video angiograms.

Automatic Segmentation of Polypoidal Choroidal Vasculopathy from Indocyanine Green Angiography Using Spatial and Temporal Patterns.

Purpose: To develop a computer-aided diagnostic tool for automated detection and quantification of polypoidal regions in indocyanine green angiography (ICGA) images.

Methods: The ICGA sequences of 59 polypoidal choroidal vasculopathy (PCV) treatment-naïve patients from five Asian countries (Hong Kong, Singapore, South Korea, Taiwan, and Thailand) were provided by the EVEREST study. The ground truth was provided by the reading center for the presence of polypoidal regions.

Complete healing of tracheoesophageal fistula in a ventilator-dependent patient by conservative treatment.

Acquired nonmalignant tracheoesophageal fistula (TEF) is a rare clinical condition with multiple etiologies, although post-intubation injury is the most common cause. TEFs can be fatal if left untreated due to devastating pulmonary complications caused by tracheobronchial contamination and poor nutrition. Herein, we present a case of complete healing of a post-intubation TEF under conservative treatment in a ventilator-dependent patient, and review previous studies regarding the treatment of acquired nonmalignant TEFs.

Real-time automatic fiducial marker tracking in low contrast cine-MV images.

Purpose: To develop a real-time automatic method for tracking implanted radiographic markers in low-contrast cine-MV patient images used in image-guided radiation therapy (IGRT).

Methods: Intrafraction motion tracking using radiotherapy beam-line MV images have gained some attention recently in IGRT because no additional imaging dose is introduced. However, MV images have much lower contrast than kV images, therefore a robust and automatic algorithm for marker detection in MV images is a prerequisite.

Retinal vascular tree reconstruction with anatomical realism.

Motivated by the goals of automatically extracting vessel segments and constructing retinal vascular trees with anatomical realism, this paper presents and analyses an algorithm that combines vessel segmentation and grouping of the extracted vessel segments. The proposed method aims to restore the topology of the vascular trees with anatomical realism for clinical studies and diagnosis of retinal vascular diseases, which manifest abnormalities in either venous and/or arterial vascular systems. Vessel segments are grouped using extended Kalman filter which takes into account continuities in curvature, width, and intensity changes at the bifurcation or crossover point.

Role of preoperative PET-CT in assessing mediastinal and hilar lymph node status in early stage lung cancer.

Background: Positron emission tomography combined with computed tomography (PET-CT) is important in the assessment and workup of lung cancer staging. However, inconsistencies between clinical image results obtained and pathologic findings of surgical specimens are still very common, particularly in patients with clinical early stage lung cancer. We sought to clarify the role of PET-CT in predicting mediastinal lymph node status preoperatively in clinical early stage lung cancer patients.

Automatic characterization of classic choroidal neovascularization by using AdaBoost for supervised learning.

Purpose: To provide a computer-aided visualization tool for accurate diagnosis and quantification of choroidal neovascularization (CNV) on the basis of fluorescence leakage characteristics.

Methods: All image frames of a fluorescein angiography (FA) sequence are first aligned and mapped to a global space. To automatically determine the severity of each pixel in the global space and hence the extent of CNV, the system matches the intensity variation of each set of spatially corresponding pixels across the sequence with the targeted leakage pattern, learned from a sampled population graded by a retina specialist.

Tumor-to-tumor metastasis: maxillary sinus adenoid cystic carcinoma metastasizing to double primary lung adenocarcinoma.

Tumor-to-tumor metastasis is a rare occurrence. The most frequent metastatic donor is lung cancer, and the most frequent recipient is renal cell carcinoma. Here we present a patient in whom lung cancer served as a metastatic recipient and maxillary sinus adenoid cystic carcinoma acted as a metastatic donor.

Optimal linear combination of facial regions for improving identification performance.

This paper presents a novel 3-D multiregion face recognition algorithm that consists of new geometric summation invariant features and an optimal linear feature fusion method. A summation invariant, which captures local characteristics of a facial surface, is extracted from multiple subregions of a 3-D range image as the discriminative features. Similarity scores between two range images are calculated from the selected subregions.