AIMC Topic: Cell Separation

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Analogous detection of circulating tumor cells using the AccuCyte -CyteFinder system and ISET system in patients with locally advanced and metastatic prostate cancer.

The Prostate
INTRODUCTION: Circulating tumor cells (CTCs) can provide important information on patient's prognosis and treatment efficacy. Currently, a plethora of methods is available for the detection of these rare cells. We compared the outcomes of two of thos...

Label-free sensor for automatic identification of erythrocytes using digital in-line holographic microscopy and machine learning.

Biosensors & bioelectronics
Cell types of erythrocytes should be identified because they are closely related to their functionality and viability. Conventional methods for classifying erythrocytes are time consuming and labor intensive. Therefore, an automatic and accurate eryt...

Autofocusing and Polar Body Detection in Automated Cell Manipulation.

IEEE transactions on bio-medical engineering
Autofocusing and feature detection are two essential processes for performing automated biological cell manipulation tasks. In this paper, we have introduced a technique capable of focusing on a holding pipette and a mammalian cell under a bright-fie...

Automated single cell isolation from suspension with computer vision.

Scientific reports
Current robots can manipulate only surface-attached cells seriously limiting the fields of their application for single cell handling. We developed a computer vision-based robot applying a motorized microscope and micropipette to recognize and gently...

Challenges in circulating tumor cell detection by the CellSearch system.

Molecular oncology
Enumeration and characterization of circulating tumor cells (CTC) hold the promise of a real time liquid biopsy. They are however present in a large background of hematopoietic cells making their isolation technically challenging. In 2004, the CellSe...

Fast Cell Segmentation Using Scalable Sparse Manifold Learning and Affine Transform-approximated Active Contour.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Efficient and effective cell segmentation of neuroendocrine tumor (NET) in whole slide scanned images is a difficult task due to a large number of cells. The weak or misleading cell boundaries also present significant challenges. In this paper, we pr...

Automated, high-throughput derivation, characterization and differentiation of induced pluripotent stem cells.

Nature methods
Induced pluripotent stem cells (iPSCs) are an essential tool for modeling how causal genetic variants impact cellular function in disease, as well as an emerging source of tissue for regenerative medicine. The preparation of somatic cells, their repr...

Robotic adherent cell injection for characterizing cell-cell communication.

IEEE transactions on bio-medical engineering
Compared to robotic injection of suspended cells (e.g., embryos and oocytes), fewer attempts were made to automate the injection of adherent cells (e.g., cancer cells and cardiomyocytes) due to their smaller size, highly irregular morphology, small t...

AI-guided laser purification of human iPSC-derived cardiomyocytes for next-generation cardiac cell manufacturing.

Communications biology
Current methods for producing cardiomyocytes from human induced pluripotent stem cells (hiPSCs) using 2D monolayer differentiation are often hampered by batch-to-batch variability and inefficient purification processes. Here, we introduce CM-AI, a no...

User-friendly image-activated microfluidic cell sorting technique using an optimized, fast deep learning algorithm.

Lab on a chip
Image-activated cell sorting is an essential biomedical research technique for understanding the unique characteristics of single cells. Deep learning algorithms can be used to extract hidden cell features from high-content image information to enabl...