Open Source Platform for Transperineal In-Bore MRI-Guided Targeted Prostate Biopsy.

Objective: Accurate biopsy sampling of the suspected lesions is critical for the diagnosis and clinical management of prostate cancer. Transperineal in-bore MRI-guided prostate biopsy (tpMRgBx) is a targeted biopsy technique that was shown to be safe, efficient, and accurate. Our goal was to develop an open source software platform to support evaluation, refinement, and translation of this biopsy approach.

DeepInfer: Open-Source Deep Learning Deployment Toolkit for Image-Guided Therapy.

Deep learning models have outperformed some of the previous state-of-the-art approaches in medical image analysis. Instead of using hand-engineered features, deep models attempt to automatically extract hierarchical representations at multiple levels of abstraction from the data. Therefore, deep models are usually considered to be more flexible and robust solutions for image analysis problems compared to conventional computer vision models.

Open-Source Platform for Prostate Motion Tracking During in-Bore Targeted MRI-Guided Biopsy.

Accurate sampling of cancer suspicious locations is critical in targeted prostate biopsy, but can be complicated by the motion of the prostate. We present an open-source software for intra-procedural tracking of the prostate and biopsy targets using deformable image registration. The software is implemented in 3D Slicer and is intended for clinical users.

In vitro evaluation of magnetic resonance imaging contrast agents for labeling human liver cells: implications for clinical translation.

Purpose: Magnetic resonance imaging (MRI) is a promising approach for non-invasive monitoring after liver cell transplantation. We compared in vitro labeling of human liver cells with nano-sized (SPIO) and micron-sized iron oxide particles (MPIO).

Procedures: The cellular iron load was quantified and phantom studies were performed using 3.