Xu Ma

Beijing Institute of Microbiology and Epidemiology | Beijing Institute of Microbiology & Epidemiology · School of Optoelectronics

Beyond extreme ultraviolet (BEUV) lithography with a 6 × nm wavelength is regarded as a future technique to continue the pattern shirking in integrated circuit (IC) manufacturing. This work proposes an optimization method for the mask structure to improve the imaging quality of BEUV lithography. Firstly, the structure of mask multilayers is optimiz...

Polarization image fusion is a crucial component of polarization imaging applications. Most of the existing polarization fusion algorithms concentrate on fusing the intensity and the degree of linear polarization (DoLP). The information encoded in the angle of linear polarization (AoLP), such as surface orientation and illumination, is not introduc...

Inverse lithography technique (ILT) is a leading-edge method to improve the image fidelity of an advanced optical lithography system by performing pixel-wise optimization on the transmission function of photomask. However, traditional ILTs are computationally intensive, which limits their application in high volume manufacturing of integrated circu...

Calculating the diffraction near field (DNF) of a three-dimensional (3D) mask is a key problem in the extreme ultraviolet (EUV) lithography imaging modeling. This paper proposes a fast DNF model of an EUV mask based on the asymmetric patch data fitting method. Due to the asymmetric imaging characteristics of the EUV lithography system, a DNF librar...

Mask three-dimensional (3D) effect is a vital influence factor of imaging performance in the advanced extreme ultraviolet (EUV) lithography system. However, the rigorous 3D mask diffraction model is very time-consuming and brings a great computational burden. This paper develops a fast and accurate method to calculate the mask diffraction near-fiel...

Coded aperture snapshot spectral imaging (CASSI) captures 3D hyperspectral images (HSIs) with 2D compressive measurements. The recovery of HSIs from these measurements is an ill-posed problem. This paper proposes a novel, to our knowledge, network architecture for this inverse problem, which consists of a multilevel residual network driven by patch...

The simulation of thick-mask diffraction near-field (DNF) is an indispensable process in aerial image calculation of immersion lithography. In practical lithography tools, the partially coherent illumination (PCI) is applied since it can improve the pattern fidelity. Therefore, it is necessary to precisely simulate the DNFs under PCI. In this paper...

Forecasting is important for social development and industrial production in today’s complex and fluctuating economic environment. The nonlinearity and non-stationarity of financial time series (FTS) data make it difficult to achieve accurate prediction. This work proposes a forecasting method for the return of FTS based on the emerging field of gr...

Long-short term memory (LSTM) network is one of the state-of-the-art models to forecast the movement of financial time series (FTS). However, existing LSTM networks do not perform well in the long-term forecasting FTS with sharp change points, which significantly influences the accumulated returns. This paper proposes a novel long-term forecasting...

Coded aperture snapshot spectral imager (CASSI) senses the spectral information of a 2D scene and captures a set of coded measurement data that can be used to reconstruct the 3D spatio-spectral datacube of the input scene by compressive sensing algorithms. The coded aperture (CA) in CASSI plays a crucial role in modulating the spatial information....

Coded aperture snapshot spectral imaging (CASSI) is a technique used to reconstruct three-dimensional hyperspectral images (HSIs) from one or several two-dimensional projection measurements. However, fewer projection measurements or more spectral channels leads to a severly ill-posed problem, in which case regularization methods have to be applied....

Coded aperture snapshot spectral imaging (CASSI) is a technique used to reconstruct three-dimensional hyperspectral images (HSIs) from one or several two-dimensional projection measurements. However, fewer projection measurements or more spectral channels leads to a severly ill-posed problem, in which case regularization methods have to be applied....

Polarized hyperspectral images contain rich information representing both surface texture and spectral signature of target scene. However, it is difficult to obtain the full-Stokes parameters of hyperspectral images directly. A compressive imaging system is proposed in this paper to recover the four-dimensional polarized hyperspectral images with f...

Phase-shifting mask (PSM) is widely used in semiconductor fabrication to improve the resolution and image fidelity of optical lithography process. However, the theoretical image fidelity limit of the PSM lithography process is not fully understood. In this paper, the information transmission mechanism of PSM layout in optical lithography system is...

Lithography is the process that transfers the structure pattern of integrated circuit device from the mask to the wafer or the surface of other semiconductor substrate, and it is the key technology to implement the mass production of high-end chips. Driven by the Moore’s law, lithography technique has stepped over multiple process nodes from 90 nm...

The thick-mask model had been used to simulate the diffraction behavior of the three-dimensional photomask in optical lithography system. By exploring the edge interference effect that appears in the diffraction near-field (DNF), an improved thick-mask model with high precision is proposed. The diffraction transfer matrix (DTM) is introduced to rep...

The effects of thick-mask and oblique incidence in extreme ultraviolet (EUV) lithography system make the aerial image calculation a challenging task. This paper develops a fast EUV lithography aerial image model based on a new kind of deep learning framework called adjoint fully convolutional network (AFCN). The AFCN consists of two adjoint data pa...

The reflective optical configuration of the coded aperture snapshot spectral imager (CASSI) based on a digital micromirror device (DMD) features both high quality and high flexibility of intensity modulation, but the image quality is always subject to off-axis aberration. This letter analyzes the formation of the off-axis aberration, and then propo...

Coded aperture X-ray computed tomography is a computational imaging technique capable of reconstructing inner structures of an object from a reduced set of X-ray projection measurements. Coded apertures are placed in front of the X-ray sources from different views and thus significantly reduce the radiation dose. This paper introduces coded apertur...

Compressive spectral X-ray imaging (CSXI) uses coded illumination projections to reconstruct tomographic images at multiple energy bins. Different K-edge materials are used to modulate the spectrum of the X-ray source at various angles, thereby capturing the projections containing spectral attenuation information. It is a cost-effective and low-dos...

Compressive spectral X-ray imaging (CSXI) introduces a pixelated spectral modulator called K-edge coded aperture (KCA) in front of the X-ray source, which enables both, lower dosage to the subject, as well as the capability of spectral tomography while using low-cost integrating X-ray detectors. CSXI systems generally use hundreds of different spec...

As the use of X-ray computed tomography (CT) grows in medical diagnosis, so does the concern for the harm a radiation dose can cause and the biological risks it represents. StaticCodeCT is a new low-dose imaging architecture that uses a single-static coded aperture (CA) in a CT gantry. It exploits the highly correlated data in the projection domain...

Hyperspectral image classification (HIC) is an active research topic in remote sensing. Hyperspectral images typically generate large data cubes posing big challenges in data acquisition, storage, transmission and processing. To overcome these limitations, this paper develops a novel deep learning HIC approach based on compressive measurements of c...

Source and mask optimization (SMO) is a widely used computational lithography technology that greatly improves the image fidelity of lithography systems. This paper develops an efficient informatics-based SMO (EISMO) method to improve the image fidelity of lithography systems. First, a communication channel model is established to depict the mechan...

Mask blank defect is one of the most important factors that degrades the image quality of extreme ultraviolet (EUV) lithography system, and further leads to a yield lose. In order to compensate the amplitude and phase distortions caused by the EUV mask blank defects, this paper proposes an advanced algorithm to optimize the mask absorber pattern ba...

Spectral clustering (SC) is a widely used technique to perform group unsupervised classification of graph signals. However, SC is sometimes computationally intensive due to the need to calculate the graph similarity matrices on large high-dimensional data sets. This paper proposes an efficient SC method that rapidly calculates the similarity matrix...

Dynamic coded x-ray tomosynthesis (CXT) uses a set of encoded x-ray sources to interrogate objects lying on a moving conveyor mechanism. The object is reconstructed from the encoded measurements received by the uniform linear array detectors. We propose a multi-objective optimization (MO) method for structured illuminations to balance the reconstru...

Compressive X-ray tomosynthesis uses a few two-dimensional projection measurements modulated by coding masks to reconstruct the three-dimensional object that can be sparsely represented on a predefined basis. However, the coding mask optimization and object reconstruction require significant computing resources. In addition, existing methods fall s...

Coded aperture X-ray CT (CAXCT) is a new low-dose imaging technology that promises far-reaching benefits in industrial and clinical applications. It places various coded apertures (CA) at a time in front of the X-ray source to partially block the radiation. The ill-posed inverse reconstruction problem is then solved using l1-norm-based iterative re...

Coded spectral X-ray computed tomography (CT) based on K-edge filtered illumination is a cost-effective approach to acquire both 3-dimensional structure of objects and their material composition. This approach allows sets of incomplete rays from sparse views or sparse rays with both spatial and spectral encoding to effectively reduce the inspection...

Coded x-ray diffraction imaging (CXRDI) is an emerging computational imaging approach that aims to solve the phase retrieval problem in x-ray crystallography based on the intensity measurements of encoded diffraction patterns. Boolean coding masks (BCMs) with complementary structures have been used to modulate the diffraction pattern in CXRDI. Howe...

Compressive x-ray tomosynthesis (CXT) uses a set of encoded projection measurements from different incident angles to reconstruct the object under inspection. We consider the variable motion of objects on a conveyor mechanism and establish an imaging model based on the sensing geometry of a dynamic CXT system. Then, a numerical algorithm is propose...

Optical lithography is a critical technique to fabricate nano-scale semiconductor devices by replicating the layouts of integrated circuits from the lithography mask onto the silicon wafer. As the critical dimension of integrated circuits continuously shrinks, source and mask optimization (SMO) methods are extensively used to improve the resolution...

Computational lithography is a key technique to optimize the imaging performance of optical lithography systems. However, the large amount of calculation involved in computational lithography significantly increases the computational complexity. This paper proposes a model-informed deep learning (MIDL) approach to improve its computational efficien...

Accuracy and reliability are the main problems to be considered when using wireless sensor networks for target tracking. Deep learning has a good prospect in visual object tracking, in which Siamese based trackers achieve a balance between performance and computational efficiency.Template adaptability and feature expression of the target are crucia...

Compressive X-ray tomosynthesis is a computational imaging technique used to reconstruct three-dimensional objects from a set of projection measurements, where the masks are used to modulate the structured illumination to reduce the radiation dose while retaining the reconstruction performance. This paper proposes a conveyor X-ray tomosynthesis ima...

Traditional compressive X-ray tomosynthesis uses sequential illumination to interrogate the object, leading to long scanning time and image distortion due to the object variation. This paper proposes a single-snapshot compressive tomosynthesis imaging approach, where the object is simultaneously illuminated by multiple X-ray emitters equipped with...

Near-field calculation for a three-dimensional (3D) mask is a fundamental task in extreme ultraviolet (EUV) lithography simulations. This paper develops a fast 3D mask near-field calculation method based on machine learning for EUV lithography. First, the training libraries of rigorous mask near fields are built based on a set of representative mas...

X-ray tomosynthesis technique can reconstruct three-dimensional object of interest from two-dimensional projection measurements. This paper proposes a compressive X-ray tomosynthesis imaging method to inspect the moving object on the conveyor. Coding masks are used to modulate the intensity distribution of X-ray sources and reduce the radiation dos...

Inverse lithography technology (ILT) is extensively used to compensate image distortion in optical lithography systems by pre-warping the photomask at the pixel scale. However, computational complexity is always a central challenge of ILT due to the big throughput of data volume. This paper proposes a dual-channel model-driven deep learning (DMDL)...

Pixelated source-mask joint optimization (SMO) plays a crucial role in improving the resolution and image fidelity of optical lithography process. However, the ever growing integration density of semiconductor devices incurs the explosion of data throughput, and poses a considerable challenge on the computational efficiency of pixelated SMO algorit...

Coded aperture X-ray computed tomography (CAXCT) systems reconstruct high quality images of the inner structure of an object from a few coded illumination measurements. Since the CT system matrix is highly structured, random coded apertures lead to lower quality image reconstructions. In this paper, the noisy forward models of CAXCT in both Gaussia...

The coded aperture snapshot spectral imager (CASSI) is a computational imaging system that acquires a three dimensional (3D) spectral data cube by a single or a few two dimensional (2D) measurements. The 3D data cube is reconstructed computationally. Binary on-off random coded apertures with square pixels are primarily implemented in CASSI systems...

Coded apertures with random patterns are extensively used in compressive spectral imagers to sample the incident scene in the image plane. Random samplings, however, are inadequate to capture the structural characteristics of the underlying signal due to the sparsity and structure nature of sensing matrices in spectral imagers. This paper proposes...

The coded aperture snapshot spectral imager (CASSI) acquires three-dimensional spectral images with two-dimensional coded projection measurements. This paper proposes an adaptive design method of the coded apertures, according to a priori knowledge of the target scene, to improve sensing efficiency and imaging performance of the super-resolution CA...

Compressive Sensing (CS) is a new paradigm for the efficient acquisition of signals that have sparse representation in a certain domain. Traditionally, CS has provided numerous methods for signal recovery over an orthonormal basis. However, modern applications have sparked the emergence of related methods for signals not sparse in an orthonormal ba...

Extreme ultraviolet (EUV) lithography is the most promising technology for next generation very-large scale integrated circuit fabrication. EUV lithography invariably introduces distortions in the projected lithographic mask patterns and thus inverse lithography tools are needed to compensate for these. This paper develops two kinds of model-based...

Photolithography is at the core of the semiconductor industry that is used to fabricate microscale and nanoscale integrated circuits. Inverse lithography is a technique extensively used to compensate for lithography patterning distortions. It refers to methods that pre-distort the photomask patterns such that their projection, through the photolith...

Extreme ultraviolet (EUV) lithography emerges as a promising technique to fabricate next-generation integrated circuits. In order to improve the lithography imaging fidelity, source optimization (SO) technique is widely used to compensate for the imaging distortion. This paper develops an efficient learning-based SO approach for EUV lithography und...

The coded aperture snapshot spectral imager (CASSI) is a computational imaging system that acquires a three dimensional (3D) spectral data cube by a single or a few two dimensional (2D) measurements. The 3D data cube is reconstructed computationally. Binary on-off random coded apertures with square pixels are primarily implemented in CASSI systems...

Image segmentation is extensively used in remote sensing spectral image processing. Most of the existing region merging methods assess the heterogeneity or homogeneity using global or pre-defined parameters, which lack the flexibility to further improve the goodness-of-fit. Recently, the local spectral angle (SA) threshold was used to produce promi...

Coded aperture snapshot spectral imager (CASSI) is a computational imaging system that acquires a three dimensional (3D) spectral data cube by single or a few two dimensional (2D) measurements. Binary random coded apertures with square pixels are primarily implemented in CASSI systems to modulate the spectral images in spatial domain. The design an...

Spectral computed tomography (SCT) is used to perform material characterization in 3D images, a feature that is not possible with conventional computed tomography (CT) systems. Currently, photon-counting detectors are used to obtain the energy binned images in SCT, however, these detectors are costly and the measured data have low signal to noise r...

Spectral computed tomography (CT) relies on the spectral dependence of X-ray attenuation coefficients to separate projection measurements into more than two energy bins. Such data can be used to unveil tomographic material characterization — key in national security and medical imaging. This paper explores a radical departure from conventional meth...

Compressive X-ray tomosynthesis is an emerging technique to reconstruct three-dimensional (3D) objects from two-dimensional projection measurements generated by a set of spatially distributed X-ray sources, where coded apertures are used in front of each source to modulate a set of X-rays to interrogate an object with a reduced radiation dose witho...

This paper explores a new approach for spectral X-ray tomography that uses structured illumination for the reconstruction of energy-binned images from fewer measurements.

Source and mask joint optimization (SMO) is a widely used computational lithography method for state-of-the-art optical lithography process to improve the yield of semiconductor wafers. Nowadays, computational efficiency has become one of the most challenging issues for the development of pixelated SMO techniques. Recently, compressive sensing (CS)...

In this paper, a new graph-spectral hyperspectral video restoration method regarding the imaging characteristics of dynamic scenes recorded by liquid crystal tunable filter hyperspectral imaging system is proposed. Firstly, the hyperspectral image of the moving foreground target is obtained by the foreground target detection, and the moving foregro...

Optical lithography is a fundamental process to fabricate integrated circuits, which are the basic fabric of the information age. Due to image distortions inherent in optical lithography, inverse lithography techniques (ILT) are extensively used by the semiconductor industry to improve lithography image resolution and fidelity in semiconductor fabr...

Liquid crystal tunable filters (LCTF) are extensively used in hyperspectral imaging systems to successively acquire different spectral components of scenes by adjusting the center wavelength of the filter. However, the spectral and spatial resolutions of the imager are limited by the bandwidth of LCTF, and the pitch dimension of the detector, respe...

Coded aperture X-ray computed tomography (CAXCT) is a novel X-ray imaging system capable of reconstructing high quality images from a reduced set of measurements. Coded apertures are placed in front of the X-ray source in CAXCT so as to obtain patterned projections onto a detector array. Then, compressive sensing (CS) reconstruction algorithms are...

Based on the strong spectral correlation between adjacent bands of hyperspectral images, we proposes a compressed sensing algorithm that uses edge information to design dynamic measurement rate to improve the reconstruction effect of compressive sensing in hyperspectral images. First, each image block is sampled at a fixed measurement rate by a ran...

Computational lithography is nowadays playing an indispensible role in improving the imaging performance of optical lithography systems. This paper develops a new and powerful approach to computational lithography by introducing an information theoretical channel modeling in partially coherent lithography systems. A statistical model is built up ba...

Optical proximity correction (OPC) is an extensively used resolution enhancement technique (RET) in optical lithography. To date, the computational efficiency has become a big issue for pixelated OPC techniques due to the increasing complexity of lithographic masks in modern integrated circuits. This paper is the first to apply nonlinear compressiv...

An efficient and robust lithography illumination optimization (ILO) approach is developed based on subspace compressive sensing (CS) and an lp-norm reconstruction algorithm. Instead of optimizing the source pattern over all its degrees of freedom, the proposed method only optimizes the source pixels in a subspace. The subspace includes the source p...

Optical lithography is extensively used in micro and nano scale semiconductor fabrication. However, the information transmission mechanism in lithography systems is not yet completely understood. This paper studies and analyzes the lithography imaging process from an information theory perspective. The optical lithography system is regarded as an i...