Computational Imaging

Computational Imaging jointly designs optics and algorithms. This field of research is inherently interdisciplinary, combining expertise in imaging science, optical engineering, signal processing and machine learning. Computational imaging can overcome physical limitations and achieve novel capabilities, from advancing experimental observation techniques used in biology, to highly novel imaging system methods to atomic force microscopy. Computational Imaging serves a broad range of scientific, defense and security, biomedical, and neuroscience applications.

Cheng & Tian’s Newest Microscopy Advance Published by Nature Communications

Professor Ji-Xin Cheng’s research group has made notable strides in improved chemical  imaging technologies, especially for medical purposes, over the last few years. Their latest, the development of a new type of mid-infrared photothermal (MIP) microscope, was published by Nature Communications in December. The paper, co-authored by collaborator and CISE affiliate Professor Lei Tian, Post-Doctoral Associate […]

Two BU Researchers Receive over $1 Million Each in Funding from the Chan Zuckerberg Initiative

Imagine being able to watch the smallest units of life—like cells and molecules—working together in real time. Seeing and measuring biological processes, a field called dynamic imaging, can help scientists unlock tremendous knowledge for treating diseases, from cancer to Alzheimer’s. In an effort to take biological imaging to the next level, two Boston University College […]

Powerful Updates to Novel Computational Imaging Device Featured in Optica

CISE affiliate Prof. Lei Tian (ECE, BME) and his team, led by PhD students, Yujia Xue (PhD, ECE, 2022) and Qianwan Yang (PhD student, ECE) published their paper “Deep-learning-augmented Computational Miniature Mesoscope” that describes advances to their Computational Miniature Mesoscope (CM2) project. This paper, published in the prestigious journal Optica, presents the CM2  V2, a […]

Professor Tian’s Paper on Adaptive 3D Descattering is the Cover Feature in Nature’s Light: Science & Applications

CISE faculty affiliate Lei Tian (ECE, BME) has published a paper entitled Adaptive 3D descattering with a dynamic synthesis network that was featured on the cover of Nature’s Light: Science & Applications.  Tian’s paper focused on training a descattering network for image recovery in scattering media using an adaptive learning framework, termed dynamic synthesis network (DSN). The framework […]

Computational Miniature Mesoscope for Cortex-wide, Cellular resolution Ca2+ Imaging in Freely Behaving Mice

Scale is a fundamental obstacle in linking neural activity to behavior. While perception and cognition arise from interactions between diverse brain areas separated by long distances, neural codes and computations are implemented at the scale of individual neurons. An integrative understanding of brain dynamics thus requires cellular-resolution measurements across sensory, motor, and executive areas spanning […]

Lighting the Way Forward for Autonomous Vehicles

CISE Faculty Affiliate Ajay Joshi with collaborators at Lightmatter and Harvard University receive $4.8M IARPA grant to develop a new Electro-Photonic Computing (EPiC) system for  AI-based navigation in Autonomous Vehicles Anyone who has ever been behind the wheel of a car knows that response time is crucial. The human sensory system needs to be fully engaged in order […]