An Accurate Perception Method for Low Contrast Bright Field Microscopy in Heterogeneous Microenvironments

Rajasekaran, Keshav; Samani, Ekta U.; Bollavaram, Manasa; Stewart, John; Banerjee, Ashis G.

doi:10.3390/app7121327

Cited by 5 publications

(2 citation statements)

References 49 publications

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“…Since one blob represents a region, and it is featured with better stability and stronger anti-noise ability than those of simple corner point. Blob detection is an important technology in computer vision which has been applied in numerous domains including medical image processing [1]- [4], video surveillance [5], [6], robotics [7]- [9], aviation systems [10]- [12], etc.…”

Section: Introductionmentioning

confidence: 99%

Blob Detection Based on Soft Morphological Filter

Tong

Chen

2020

IEICE Trans. Inf. & Syst.

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Blob detection is an important part of computer vision and a special case of region detection with important applications in the image analysis. In this paper, the dilation operator in standard mathematical morphology is firstly extended to the order dilation operator of soft morphology, three soft morphological filters are designed by using the operator, and a novel blob detection algorithm called SMBD is proposed on that basis. SMBD had been proven to have better performance of anti-noise and blob shape detection than similar blob filters based on mathematical morphology like Quoit and N-Quoit in terms of theoretical and experimental aspects. Additionally, SMBD was also compared to LoG and DoH in different classes, which are the most commonly used blob detector, and SMBD also achieved significantly great results.

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Section: Introductionmentioning

confidence: 99%

Blob Detection Based on Soft Morphological Filter

Tong

Chen

2020

IEICE Trans. Inf. & Syst.

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“…2019, 9, 2883 2 of 15 focusing the laser on the cell [20][21][22], in which laser beams act as special end-effectors. Using the direct technique, a large number of cells can be manipulated individually or simultaneously in a series or parallel manner with high precision and high efficiency [23,24]. However, direct manipulation by the high focused laser beams may cause photobleaching and photodamage to the cells.…”

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confidence: 99%

Automated Indirect Transportation of Biological Cells with Optical Tweezers and a 3D Printed Microtool

Xie

Wei

et al. 2019

Applied Sciences

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Optical tweezers are widely used for noninvasive and precise micromanipulation of living cells to understand biological processes. By focusing laser beams on cells, direct cell manipulation with optical tweezers can achieve high precision and flexibility. However, direct exposure to the laser beam can lead to negative effects on the cells. These phenomena are also known as photobleaching and photodamage. In this study, we proposed a new indirect cell micromanipulation approach combined with a robot-aided holographic optical tweezer system and 3D nano-printed microtool. The microtool was designed with a V-shaped head and an optical handle part. The V-shaped head can push and trap different sizes of cells as the microtool moves forward by optical trapping of the handle part. In this way, cell exposure to the laser beam can be effectively reduced. The microtool was fabricated with a laser direct writing system by two-photon photopolymerization. A control strategy combined with an imaging processing algorithm was introduced for automated manipulation of the microtool and cells. Experiments were performed to verify the effectiveness of our approach. First, automated microtool transportation and rotation were demonstrated with high precision. Second, indirect optical transportations of cells, with and without an obstacle, were performed to demonstrate the effectiveness of the proposed approach. Third, experiments of fluorescent cell manipulation were performed to confirm that, indicated by the photobleaching effect, indirect manipulation with the microtool could induce less laser exposure compared with direct optical manipulation. The proposed method could be useful in complex biomedical applications where precise cell manipulation and less laser exposure are required.

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A machine learning approach to analyze the structural formation of soft matter via image recognition

Terao

2020

Soft Materials

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An Accurate Perception Method for Low Contrast Bright Field Microscopy in Heterogeneous Microenvironments

Cited by 5 publications

References 49 publications

Blob Detection Based on Soft Morphological Filter

Blob Detection Based on Soft Morphological Filter

Automated Indirect Transportation of Biological Cells with Optical Tweezers and a 3D Printed Microtool

A machine learning approach to analyze the structural formation of soft matter via image recognition

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