Results 91 to 100 of about 719,917 (315)
To explore the impact of the overexpression of the multidrug‐transporter P‐glycoprotein (ABCB1) on membrane fluidity, we compared the transversal gradient of mobility and microviscosity in plasma membranes of drug‐sensitive Chinese hamster ovary cells (AuxB1) and their multidrug‐resistant derivatives (B30) using the fluorescent n‐(9‐anthroyloxy) fatty ...
Roger Busche+2 more
wiley +1 more source
E-consumer segmentation: an applied study based in the internet use perspectives
The market segmentation has frequently been used in the traditional marketing research but still appears as a relatively new subject in the Information and Communication Technologies (ICT) and Internet environment.
Eduard Cristóbal-Fransi+2 more
doaj +1 more source
Segmentation Ability Map: Interpret deep features for medical image segmentation [PDF]
Deep convolutional neural networks (CNNs) have been widely used for medical image segmentation. In most studies, only the output layer is exploited to compute the final segmentation results and the hidden representations of the deep learned features have not been well understood.
arxiv
LVIS: A Dataset for Large Vocabulary Instance Segmentation [PDF]
Progress on object detection is enabled by datasets that focus the research community’s attention on open challenges. This process led us from simple images to complex scenes and from bounding boxes to segmentation masks. In this work, we introduce LVIS (
Agrim Gupta+2 more
semanticscholar +1 more source
The number of circulating tumor cells obtained from prostate cancer patients was increased approximately 5‐fold compared to regular CellSearch when processing 2 mL diagnostic leukapheresis material aliquots and increased by 44‐fold when processing 20 mL DLA aliquots using the flow enrichment target capture Halbach‐array.
Michiel Stevens+8 more
wiley +1 more source
Data Balancing Based on Pre-Training Strategy for Liver Segmentation from CT Scans
Data imbalance is often encountered in deep learning process and is harmful to model training. The imbalance of hard and easy samples in training datasets often occurs in the segmentation tasks from Contrast Tomography (CT) scans.
Yong Zhang+6 more
doaj +1 more source
Image Segmentation Algorithms Overview [PDF]
The technology of image segmentation is widely used in medical image processing, face recognition pedestrian detection, etc. The current image segmentation techniques include region-based segmentation, edge detection segmentation, segmentation based on clustering, segmentation based on weakly-supervised learning in CNN, etc.
arxiv
We quantified and cultured circulating tumor cells (CTCs) of 62 patients with various cancer types and generated CTC‐derived tumoroid models from two salivary gland cancer patients. Cellular liquid biopsy‐derived information enabled molecular genetic assessment of systemic disease heterogeneity and functional testing for therapy selection in both ...
Nataša Stojanović Gužvić+31 more
wiley +1 more source
Prefer Nested Segmentation to Compound Segmentation [PDF]
Introduction: Intra-organ radiation dose sensitivity is becoming increasingly relevant in clinical radiotherapy. One method for assessment involves partitioning delineated regions of interest and comparing the relative contributions or importance to clinical outcomes.
arxiv
Crosstalk between gut microbiota and tumor: tumors could cause gut dysbiosis and metabolic imbalance
In this research, we analyzed the relationship between gut microbiota and tumor. We discovered that both subcutaneous and metastatic tumors would alter the composition and metabolic function of gut microbiota. Meanwhile, fecal microbiota transplantation also indicated the anti‐tumor role of the gut microbiota, revealing the crosstalk between tumor and ...
Siyuan Zhang+8 more
wiley +1 more source