The ability to classify and map numerous cell types as well as healthy and diseased cells can bring significant insight to biology and medicine. While single-cell sequencing becomes cornerstone for cell classification and mapping, isolation of interested cells for genomic analyses rely on fluorescence activated cell sorting (FACS), which can only isolate cells based on integrated intensities. The availability of flow cytometers with the capability to classify and isolate cells guided by high-content cell images is enabling and transformative. It provides a new paradigm to allow researchers and clinicians to isolate cells using multiple user-defined characteristics encoded by both fluorescent signals and morphological and spatial features. In this thesis, we demonstrated the “Image-Guided Cell Classification and Sorting” technology. This technology possesses high throughput isolation capability of FACS and high information content of microscopy. To achieve “Image-Guided Cell Classification and Sorting”, we combined the techniques of machine learning, photonics, real-time signal processing and microfluidics.

Abstract: Single-cell dispensing for automated cell isolation of individual cells has gained increased attention in the biopharmaceutical industry, mainly for production of clonal cell lines. Here, machine learning for classification of cell images is applied for 'real-time' cell viability sorting on a single-cell printer. We show that an extremely shallow convolutional neural network (CNN) for classification of low-complexity cell images outperforms more complex architectures. Datasets with hundreds of cell images from four different samples were used for training and validation of the CNNs. The clone recovery, i.e. the fraction of single-cells that grow to clonal colonies, is predicted to increase for all the samples investigated. Finally, a trained CNN was deployed on a c.sight single-cell printer for 'real-time' sorting of a CHO-K1 cells. On a sample with artificially damaged cells the clone recovery could be increased from 27% to 73%, thereby resulting in a significantly faster and more efficient cloning. Depending on the classification threshold, the frequency at which viable cells are dispensed could be increased by up to 65%. This technology for image-based cell sorting is highly versatile and can be expected to enable cell sorting by computer vision with respect to different criteria in the future

The analysis and sorting of large numbers of cells with a fluorescence-activated cell sorter (FACS) was first achieved some 30 years ago. Since then, this technology has been rapidly developed and is used today in many laboratories. A Springer Lab Manual Review of the First Edition: "This is a most useful volume which will be a welcome addition for personal use and also for laboratories in a wide range of disciplines. Highly recommended." CYTOBIOS

This book delves into the recent developments in the microscale and microfluidic technologies that allow manipulation at the single and cell aggregate level. Expert authors review the dominant mechanisms that manipulate and sort biological structures, making this a state-of-the-art overview of conventional cell sorting techniques, the principles of microfluidics, and of microfluidic devices. All chapters highlight the benefits and drawbacks of each technique they discuss, which include magnetic, electrical, optical, acoustic, gravity/sedimentation, inertial, deformability, and aqueous two-phase systems as the dominant mechanisms utilized by microfluidic devices to handle biological samples. Each chapter explains the physics of the mechanism at work, and reviews common geometries and devices to help readers decide the type of style of device required for various applications. This book is appropriate for graduate-level biomedical engineering and analytical chemistry students, as well as engineers and scientists working in the biotechnology industry.

This detailed volume for the first time explores techniques and protocols involving quantitative imaging flow cytometry (IFC), which has revolutionized our ability to analyze cells, cellular clusters, and populations in a remarkable fashion. Beginning with an introduction to technology, the book continues with sections addressing protocols for studies on the cell nucleus, nucleic acids, and FISH techniques using an IFC instrument, immune response analysis and drug screening, IFC protocols for apoptosis and cell death analysis, as well as morphological analysis and the identification of rare cells. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Imaging Flow Cytometry: Methods and Protocols will be a critical source for all laboratories seeking to implement IFC in their research studies.

This book introduces new techniques for cellular image feature extraction, pattern recognition and classification. The authors use the antinuclear antibodies (ANAs) in patient serum as the subjects and the Indirect Immunofluorescence (IIF) technique as the imaging protocol to illustrate the applications of the described methods. Throughout the book, the authors provide evaluations for the proposed methods on two publicly available human epithelial (HEp-2) cell datasets: ICPR2012 dataset from the ICPR'12 HEp-2 cell classification contest and ICIP2013 training dataset from the ICIP'13 Competition on cells classification by fluorescent image analysis. First, the reading of imaging results is significantly influenced by one’s qualification and reading systems, causing high intra- and inter-laboratory variance. The authors present a low-order LP21 fiber mode for optical single cell manipulation and imaging staining patterns of HEp-2 cells. A focused four-lobed mode distribution is stable and effective in optical tweezer applications, including selective cell pick-up, pairing, grouping or separation, as well as rotation of cell dimers and clusters. Both translational dragging force and rotational torque in the experiments are in good accordance with the theoretical model. With a simple all-fiber configuration, and low peak irradiation to targeted cells, instrumentation of this optical chuck technology will provide a powerful tool in the ANA-IIF laboratories. Chapters focus on the optical, mechanical and computing systems for the clinical trials. Computer programs for GUI and control of the optical tweezers are also discussed. to more discriminative local distance vector by searching for local neighbors of the local feature in the class-specific manifolds. Encoding and pooling the local distance vectors leads to salient image representation. Combined with the traditional coding methods, this method achieves higher classification accuracy. Then, a rotation invariant textural feature of Pairwise Local Ternary Patterns with Spatial Rotation Invariant (PLTP-SRI) is examined. It is invariant to image rotations, meanwhile it is robust to noise and weak illumination. By adding spatial pyramid structure, this method captures spatial layout information. While the proposed PLTP-SRI feature extracts local feature, the BoW framework builds a global image representation. It is reasonable to combine them together to achieve impressive classification performance, as the combined feature takes the advantages of the two kinds of features in different aspects. Finally, the authors design a Co-occurrence Differential Texton (CoDT) feature to represent the local image patches of HEp-2 cells. The CoDT feature reduces the information loss by ignoring the quantization while it utilizes the spatial relations among the differential micro-texton feature. Thus it can increase the discriminative power. A generative model adaptively characterizes the CoDT feature space of the training data. Furthermore, exploiting a discriminant representation allows for HEp-2 cell images based on the adaptive partitioned feature space. Therefore, the resulting representation is adapted to the classification task. By cooperating with linear Support Vector Machine (SVM) classifier, this framework can exploit the advantages of both generative and discriminative approaches for cellular image classification. The book is written for those researchers who would like to develop their own programs, and the working MatLab codes are included for all the important algorithms presented. It can also be used as a reference book for graduate students and senior undergraduates in the area of biomedical imaging, image feature extraction, pattern recognition and classification. Academics, researchers, and professional will find this to be an exceptional resource.

The most mature, widespread sorting technology, fluorescence-activated cell sorting (FACS), offers high throughput and sorts predicated on a wide range of phenotypes that can be conveyed through average cellular fluorescence or light scattering levels. However, FACS cannot detect a wide range of phenotypes easily observable through microscopy, such as details of cell morphology, sub-cellular localization, and temporal fluorescence expression with single-cell resolution. Presently, there is no widespread, user-friendly technique to sort cells following microscopy. Commercial solutions offering this capability are prohibitively expensive to individual labs, and are most likely to be found only in well-resourced core facilities. This thesis presents the design, implementation, and testing of three new technologies for simple, inexpensive, viable, image-predicated cell sorting that can be disseminated to individual labs. For anchorage-dependent cells, we have implemented two technologies. The first is a method termed polymerization-activated cell sorting, or PACS, that permits the selective hydrogel-mediated photo-encapsulation of undesired cells in a culture dish and the retrieval of desired cells using enzyme-mediated release. The second is a method termed radical-activated cell sorting, or RACS, that permits the light-mediated killing of undesired cells in a culture dish through photo patterning of radical toxicity. For non-anchorage-dependent cells, we have developed optofluidic cell sorting, or optoflucs. In this approach, cells are injected into a microfluidic device where they are allowed to settle into an array of cell-sized microwells. A laser is then used to optically levitate desired cells out of the array and into a flow stream for collection. This thesis demonstrates> 100-fold enrichment of target cell populations and up to 89% output purity following a single round of image-predicated, viable cell sorting. In addition, this thesis demonstrates examples of sorts predicated on fluorescence localization, a phenotype that cannot be sorted using FACS. These results, coupled with the minimal expense and simplicity of these technologies make these techniques appealing for widespread adoption by individual biology labs.

Stimulated Raman Scattering Microscopy: Techniques and Applications describes innovations in instrumentation, data science, chemical probe development, and various applications enabled by a state-of-the-art stimulated Raman scattering (SRS) microscope. Beginning by introducing the history of SRS, this book is composed of seven parts in depth including instrumentation strategies that have pushed the physical limits of SRS microscopy, vibrational probes (which increased the SRS imaging functionality), data science methods, and recent efforts in miniaturization. This rapidly growing field needs a comprehensive resource that brings together the current knowledge on the topic, and this book does just that. Researchers who need to know the requirements for all aspects of the instrumentation as well as the requirements of different imaging applications (such as different types of biological tissue) will benefit enormously from the examples of successful demonstrations of SRS imaging in the book. Led by Editor-in-Chief Ji-Xin Cheng, a pioneer in coherent Raman scattering microscopy, the editorial team has brought together various experts on each aspect of SRS imaging from around the world to provide an authoritative guide to this increasingly important imaging technique. This book is a comprehensive reference for researchers, faculty, postdoctoral researchers, and engineers. - Includes every aspect from theoretic reviews of SRS spectroscopy to innovations in instrumentation and current applications of SRS microscopy - Provides copious visual elements that illustrate key information, such as SRS images of various biological samples and instrument diagrams and schematics - Edited by leading experts of SRS microscopy, with each chapter written by experts in their given topics