Utilization segmentation

Magnetic Resonance Imaging (MRI) plays an important role in neurology, particularly in the precise segmentation of brain tissues. Accurate segmentation is crucial for diagnosing brain injuries and neurodegenerative conditions. We introduce an Enhanced Spatial Fuzzy C-means (esFCM) algorithm for 3D T1 MRI segmentation to three tissues, i.e. White Matter (WM), Gray Matter (GM), and Cerebrospinal Fluid (CSF). The esFCM employs a weighted least square algorithm utilizing the Structural Similarity Index (SSIM) for polynomial bias field correction...

The hollow fiber filter is the primary cell-retention device used in high-density perfusion cell culture and often used in an alternating tangential flow (ATF) configuration. The limited commercially available diaphragm pumps for ATF prevent utilization of vertical space when scaling beyond 500 L. Stacking hollow fiber filters coupled with viscous cell culture imposes vacuum pressure exceeding facility capabilities. Additionally, the longer filter assembly increases the hold-up volume and exceeds the diaphragm pump's fluid exchange capacity...

INTRODUCTION: Patients with chronic pain frequently report cognitive symptoms that affect memory and attention, which are functions attributed to the hippocampus. Trigeminal neuralgia (TN) is a chronic neuropathic pain disorder characterized by paroxysmal attacks of unilateral orofacial pain. Given the stereotypical nature of TN pain and lack of negative symptoms including sensory loss, TN provides a unique model to investigate the hippocampal implications of chronic pain. Recent evidence demonstrated that TN is associated with macrostructural hippocampal abnormalities indicated by reduced subfield volumes; however, there is a paucity in our understanding of hippocampal microstructural abnormalities associated with TN...

Microvascular networks are challenging to model because these structures are currently near the diffraction limit for most advanced three-dimensional imaging modalities, including confocal and light sheet microscopy. This makes semantic segmentation difficult, because individual components of these networks fluctuate within the confines of individual pixels. Level set methods are ideally suited to solve this problem by providing surface and topological constraints on the resulting model, however these active contour techniques are extremely time intensive and impractical for terabyte-scale images...

PURPOSE: We aimed to evaluate the clinical efficacy of bilateral decompression with minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF) assisted by an ultrasonic bone curette (UBC) for treating severe degenerative lumbar spinal stenosis (DLSS) and traditional tool laminectomy decompression MIS-TLIF for treating severe DLSS. METHODS: The clinical data of 128 patients with single-segment severe DLSS who were admitted between January 2017 and December 2021 were retrospectively analyzed...

OBJECTIVE: To forecast the annual burden of type 2 diabetes and related socio-demographic disparities in Belgium until 2030. METHODS: This study utilized a discrete-event transition microsimulation model. A synthetic population was created using 2018 national register data of the Belgian population aged 0-80 years, along with the national representative prevalence of diabetes risk factors obtained from the latest (2018) Belgian Health Interview and Examination Surveys using Multiple Imputation by Chained Equations (MICE) as inputs to the Simulation of Synthetic Complex Data (simPop) model...

In the field of skin lesion image segmentation, accurate identification and partitioning of diseased regions is of vital importance for in-depth analysis of skin cancer. Self-supervised learning, i.e., MAE, has emerged as a potent force in the medical imaging domain, which autonomously learns and extracts latent features from unlabeled data, thereby yielding pre-trained models that greatly assist downstream tasks. To encourage pre-trained models to more comprehensively learn the global structural and local detail information inherent in dermoscopy images, we introduce a Teacher-Student architecture, named TEDMAE, by incorporating a self-distillation mechanism, it learns holistic image feature information to improve the generalizable global knowledge learning of the student MAE model...

Orthodontic uprighting or traction of an impacted mandibular second molar often necessitates invasive interventions. This report aims to illustrate the utilization of nickel-titanium wire segments inserted into small, simple tubes for uprighting mesially impacted mandibular second molars and also for scissor bite correction. The term "simple tube" refers to a tube without a bonding base attached to a tooth surface by covering it with flowable composite resin. Due to the absence of a bonding base, the simple tube is characterized by its diminutive size and minimal profile height, facilitating placement on partially exposed second molars and unconventional positioning to adjust the force geometry...

Proximal femoral fracture segmentation in computed tomography (CT) is essential in the preoperative planning of orthopedic surgeons. Recently, numerous deep learning-based approaches have been proposed for segmenting various structures within CT scans. Nevertheless, distinguishing various attributes between fracture fragments and soft tissue regions in CT scans frequently poses challenges, which have received comparatively limited research attention. Besides, the cornerstone of contemporary deep learning methodologies is the availability of annotated data, while detailed CT annotations remain scarce...

To enhance M-mode echocardiography's utility for measuring cardiac structures, we developed and evaluated an artificial intelligence (AI)-based automated analysis system for M-mode images through the aorta and left atrium [M-mode (Ao-LA)], and through the left ventricle [M-mode (LV)]. Our system, integrating two deep neural networks (DNN) for view classification and image segmentation, alongside an auto-measurement algorithm, was developed using 5,958 M-mode images [3,258 M-mode (LA-Ao), and 2,700 M-mode (LV)] drawn from a nationwide echocardiographic dataset collated from five tertiary hospitals...

Evaluating the heterogeneity of extracellular vesicles (EVs) is crucial for unraveling their complex actions and biodistribution. Here, we identify consistent architectural heterogeneity of EVs using cryogenic transmission electron microscopy (cryo-TEM), which has an inherent ability to image biological samples without harsh labeling methods while preserving their native conformation. Imaging EVs isolated using different methodologies from distinct sources, such as cancer cells, normal cells, immortalized cells, and body fluids, we identify a structural atlas of their dominantly consistent shapes...

The management of lymphatic fistulas following surgical procedures, in particular after inguinal lymphadenectomy, represents a significant clinical challenge. The current case report shows the novel use of the superficial circumflex iliac perforator (SCIP) pedicle vein for lymphovenous anastomosis (LVA) to treat a chronic inguinal lymphatic fistula in a 58-year-old male patient. This patient had developed a persistent lymphorrhea and wound dehiscence after a right inguinal lymph node biopsy performed for oncological reasons 1...

Radiological imaging to examine intracranial blood vessels is critical for preoperative planning and postoperative follow-up. Automated segmentation of cerebrovascular anatomy from Time-Of-Flight Magnetic Resonance Angiography (TOF-MRA) can provide radiologists with a more detailed and precise view of these vessels. This paper introduces a domain generalized artificial intelligence (AI) solution for volumetric monitoring of cerebrovascular structures from multi-center MRAs. Our approach utilizes a multi-task deep convolutional neural network (CNN) with a topology-aware loss function to learn voxel-wise segmentation of the cerebrovascular tree...

PURPOSE: This study aims to establish DROL (disruption of retinal outer layers), PROS (photoreceptor outer segment length), SND (subfoveal neuroretinal detachment), and hyperreflective walls of foveal cystoid spaces (HRW) as optical coherence tomography (OCT) biomarkers and predictors of central macular thickness (CMT) and visual acuity in diabetic macular edema (DME) treated with intravitreal ranibizumab (IVR). METHODS: In this prospective, interventional study performed at a tertiary care center over a span of 1 year from December 2021 to December 2022, 50 eyes of 46 patients of DME were included...

The solid-state battery with a lithium metal anode is a promising candidate for next-generation batteries with improved energy density and safety. However, the current polymer electrolytes still cannot fulfill the demands of solid-state batteries. In this work, we propose a "5H" poly(ethylene oxide) (PEO) electrolyte via introducing a multifunctional additive of tris(pentafluorophenyl)borane (TPFPB) for high-performance lithium metal batteries. The addition of TPFPB improves the ionic conductivity from 6.08 × 10-5 to 1...

PURPOSE: To investigate the effectiveness and safety of separation surgery for Epidural Spinal Cord Compression (ESCC) graded ≥ 2 in patients with Multiple Myeloma (MM), analyze factors influencing surgical outcomes, and develop a preliminary treatment decision framework for these patients. METHODS: A retrospective analysis was conducted on clinical data from 35 MM patients who underwent separation surgery for ESCC graded ≥ 2 between 2013 and 2018...

Endovascular treatment of complex vascular anomalies shifts the risk of open surgical procedures to the benefit of minimally invasive endovascular procedural solutions. Complex open surgical procedures used to be the only option for the treatment of a myriad of conditions like pulmonary and aortic valve replacement as well as cerebral aneurysm repair. However, due to advancements in catheter-delivered devices and operator expertise, these procedures (along with many others) can now be performed through minimally invasive procedures delivered through a central or peripheral vein or artery...

Bleomycin (BLM)-induced lung injury in mice is a valuable model for investigating the molecular mechanisms that drive inflammation and fibrosis and for evaluating potential therapeutic approaches to treat the disease. Given high variability in the BLM model, it is critical to accurately phenotype the animals in the course of an experiment. In the current study, we aimed to demonstrate the utility of microscopic computed tomography (µCT) imaging combined with an artificial intelligence (AI) convolutional neural network (CNN)-powered lung segmentation for rapid phenotyping of BLM mice...

The field of theranostics is rapidly advancing, driven by the goals of enhancing patient care. Recent breakthroughs in artificial intelligence (AI) and its innovative theranostic applications have marked a critical step forward in nuclear medicine, leading to a significant paradigm shift in precision oncology. For instance, AI-assisted tumor characterization, including automated image interpretation, tumor segmentation, feature identification, and prediction of high-risk lesions, improves diagnostic processes, offering a precise and detailed evaluation...

Given the high risk of complications associated with cesarean hysterectomy for placenta accreta spectrum (PAS), any surgical approach and technique can yield utility in reducing the surgical morbidity. Here, we propose the 3-2-1 approach as a schema to be implemented in the proper setting for the surgical management of a PAS cesarean hysterectomy. The 3-2-1 approach begins with the surgical dissection of three anatomical landmarks that ultimately facilitate a safe surgical site for the ligation and transection of the uterine vessels...