Publications by authors named "Hossein Najafiaghdam"

We present a mm-sized, ultrasonically powered lensless CMOS image sensor as a progress towards wireless fluorescence microscopy. Access to biological information within the tissue has the potential to provide insights guiding diagnosis and treatment across numerous medical conditions including cancer therapy. This information, in conjunction with current clinical imaging techniques that have limitations in obtaining images continuously and lack wireless compatibility, can improve continual detection of multicell clusters deep within tissue.

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We present a mm-sized, ultrasonically powered lensless CMOS image sensor as a progress towards wireless fluorescence microscopy. Access to biological information within the tissue has the potential to provide insights guiding diagnosis and treatment across numerous medical conditions including cancer therapy. This information, in conjunction with current clinical imaging techniques that have limitations in obtaining images continuously and lack wireless compatibility, can improve continual detection of multicell clusters deep within tissue.

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Millimeter-scale multi-cellular level imagers enable various applications, ranging from intraoperative surgical navigation to implantable sensors. However, the tradeoffs for miniaturization compromise resolution, making extracting 3D cell locations challenging-critical for tumor margin assessment and therapy monitoring. This work presents three machine-learning-based modules that extract spatial information from single image acquisitions using custom-made millimeter-scale imagers.

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We present an optics-free CMOS image sensor that incorporates a novel time-gated dual-photodiode pixel design to allow filter- and lens-less image acquisition of near-infrared-excited (NIR-excited) upconverting nanoparticles. Recent biomedical advances have highlighted the benefits of NIR excitation, but NIR interaction with silicon has remained a challenge, even with high-performance optical blocking filters. Using a secondary diode and a dual-photodiode design, this sensor is able to remove the 100s of mV of NIR background on pixels and bring it down to single-digit mV level, nearing its noise floor of 2.

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Purpose: Intraoperative detection and removal of microscopic residual disease (MRD) remain critical to the outcome of cancer surgeries. Today's minimally invasive surgical procedures require miniaturization and surgical integration of highly sensitive imagers to seamlessly integrate into the modern clinical workflow. However, current intraoperative imagers remain cumbersome and still heavily dependent on large lenses and rigid filters, precluding further miniaturization and integration into surgical tools.

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Real-time monitoring of cellular-level changes inside the body provides key information regarding disease progression and therapy assessment for critical care including cancer therapy. Current state-of-the-art oncological imaging methods impose unnecessary latencies to detect small cell foci. Invasive methods such as biopsies, on the other hand, cause disruption if deployed on a repeated basis.

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Intraoperative visualization in small surgical cavities and hard-to-access areas are essential requirements for modern, minimally invasive surgeries and demand significant miniaturization. However, current optical imagers require multiple hard-to-miniaturize components including lenses, filters and optical fibers. These components restrict both the form-factor and maneuverability of these imagers, and imagers largely remain stand-alone devices with centimeter-scale dimensions.

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Optimal cancer therapy requires targeted and individualized treatment of all tumor cells, including both gross and microscopic disease. Intraoperatively hard to visualize and often left behind, microscopic foci of residual cancer cells significantly increase the risk of cancer recurrence and treatment failure rates. Fluorescently-tagged targeted molecular labels are employed to guide surgery, but conventional fluorescent intraoperative imagers suffer from lack of sensitivity and maneuverability, limiting practicality in small tumor cavities owing to their cumbersome sizes driven by optics.

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Multiphoton imaging techniques that convert low-energy excitation to higher energy emission are widely used to improve signal over background, reduce scatter, and limit photodamage. Lanthanide-doped upconverting nanoparticles (UCNPs) are among the most efficient multiphoton probes, but even UCNPs with optimized lanthanide dopant levels require laser intensities that may be problematic. Here, we develop protein-sized, alloyed UCNPs (aUCNPs) that can be imaged individually at laser intensities >300-fold lower than needed for comparably sized doped UCNPs.

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