Because of improved display quality, the smartphone has been advocated by medical imaging vendors for viewing medical images in specific conditions that require urgency of results, or when full-sized workstation displays are not readily available. As a handheld device, the viewing conditions of a smartphone (e.g. ambient light and handshaking) are not predictable, and may adversely affect the perceived image quality.
The present invention proposes the use of the built-in sensors in iPhone-like mobile devices to detect and adapt to the viewing conditions and handshaking. The LightCensor algorithm, when used in a mobile device, enhances the capabilities of the device to be used for medical imaging.
The device’s built-in camera can be used to capture the ambient light for determining the adaptation level, which affects the brightness, contrast, and color perception. The built-in accelerometers can be used to detect orientation and moving velocity of the display, which affect the perceived spatial resolution. The execution of critical tasks can then be censored based on the detected scenario. If the viewing conditions are not suitable for reading medical images, for example, then the program could halt until the viewing conditions improve. This invention can be used by consumer-grade mobile devices that were not originally designed for medical purposes to show medical images with improved perceived image quality.