Dynamic Structured Illumination Microscopy with a Neural Space-time Model

A new structured illumination microscopy (SIM) method, Speckle Flow SIM, that uses static patterned illumination on a dynamic scene and models the space-time relationship to super-resolve the dynamic scene.

Self-calibrated 3D differential phase contrast microscopy with optimized illumination

A practical extension of the 3D DPC method that does not require a precise motion stage for scanning the focus and uses optimized illumination patterns for improved 3D refractive index tomography.

GU Radiologists vs AI in Detection of Prostate Cancer on MRI

A validation study of our previously developed algorithm for prostate cancer detection using an independent patient cohort who went through radical prostatectomy and compared with genitourinary radiologists under the same setting.

Joint Prostate Cancer Detection and Histological Score Prediction on MRI

We proposed a multi-class CNN to jointly detect prostate cancer lesions and characterizes their histopathological aggressiveness by fully utilizing distinctive knowledge from multi-parametric MRI.

Interpreting CNN Knowledge via an Explanatory Graph

We proposed to automatically discover object parts in an unsupervised manner, which disentangles feature components of object parts from feature representations of each convolutional filter.

Mining Object Parts from CNNs via Active Question-Answering

We used active question-answering to weakly-supervised semanticize neural patterns in conv-layers of the CNN and mine part concepts.