Flow cytometry is one of the most used and powerful equipment in cell counting and biomarker detection, and fluorescent-activated cell sorter (FACS) allows users to sort out single cells based on user-defined features. Despite its high throughput, the lack of cell image information may result in false-positive and false-negative, which limits the application of FACS. As a result, imaging flow cytometer (IFC) was developed for imaging of large cell volume in the flow system. However, the integration of sorting function and 3-dimensional (3D) imaging capabilities in IFC remains to be challenged. Here we developed 2-dimensional (2D) image-guided cell sorters, and 3D imaging flow cytometer, which will be eventually upgraded to a cell sorter based on 3D images. Chapter 2 describes a microfluidic cell sorter that uses fast scanning laser excitation sources and photomultiplier tubes, coupled with real-time image processing, to image and sort cells based on user-defined spatial features. However, flow confinement for most microfluidic devices is generally only one-dimensional using sheath flow. As a result, the equilibrium distribution of cells spreads beyond the focal plane of commonly used Gaussian laser excitation beams, resulting in a large number of blurred images that hinder subsequent cell sorting based on cell image features. To address this issue, chapter 3 presents a Bessel Gaussian beam image-guided cell sorter with an ultra-long depth of focus, enabling focused images of >85% of passing cells.IFC that can isolate cells of interest in a label-free environment would simplify the process flow, reduce cost, minimize cell disruptions by labeling, and overcome limitations of biomarker availability and specificity. On the other hand, collapsing 3D cell volume to 2D images always greatly reduces information content. To address these needs, we developed a label-free 3D imaging flow cytometer and presented it in chapter 4. The array of photomultiplier tubes (PMTs) collected forward scattering signals from multiple imaging depths, which were reconstructed by software to 3D cell image.