Abstract: A fluid level sensor for sensing a level of a fluid within a toroid-shaped tank includes a float ring, a float structure, a gauge shaft, and a tiller arm. The float ring rotate s within the toroid-shaped tank about a first rotational axis. The float structure exhibits buoyancy in the fluid disposed within the toroid-shaped tank and supplies a force to the float ring based on the level of the fluid within the toroid-shaped tank. The gauge shaft is mounted for rotation about a second rotational axis and rotates about the second rotational axis to a position representative of the level of the fluid within the toroid-shaped tank. The tiller arm supplies the rotational drive force to the gauge shaft when the float ring rotates.

Abstract: Systems and techniques for generating and/or employing a medical imaging stroke model are presented. In one example, a system employs a convolutional neural network to generate output data regarding a brain anatomical region based on diffusion-weighted imaging (DWI) data associated with the brain anatomical region and apparent diffusion coefficient (ADC) data associated with the brain anatomical region. The system also detects presence or absence of a medical stroke condition associated with the brain anatomical region based on the output data.

Abstract: Systems and techniques for generating and/or employing a medical imaging stroke model are presented. In one example, a system employs a convolutional neural network to generate output data regarding a brain anatomical region based on diffusion-weighted imaging (DWI) data associated with the brain anatomical region and apparent diffusion coefficient (ADC) data associated with the brain anatomical region. The system also detects presence or absence of a medical stroke condition associated with the brain anatomical region based on the output data.

Abstract: Systems and techniques for generating and/or employing a computed tomography (CT) medical imaging intracranial hemorrhage model are presented. In one example, a system employs a convolutional neural network to generate classification output data regarding a brain anatomical region based on computed tomography (CT) data associated with the brain anatomical region. The system also detects presence or absence of a medical intracranial hemorrhage condition in the CT data based on the classification output data. Furthermore, the system determines a subtype of the medical intracranial hemorrhage condition based on the classification output data. The system also generates display data associated with the subtype of the medical intracranial hemorrhage condition in a human-interpretable format.