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Image Formation and Processing Flashcards

7 cards from real ARDMS SPI practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.

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  1. What is the primary function of the scan converter in a diagnostic ultrasound system?

    Answer: Convert polar ultrasound data into a rectangular display format

    The scan converter maps echo data from the polar coordinate geometry of the transducer sweep into the Cartesian (rectangular) format used by the video display.

  2. Which parameter directly determines the number of pixels used to represent a digital ultrasound image?

    Answer: Matrix size

    Matrix size (e.g., 512×512 or 1024×1024) defines the total number of pixels in the digital image grid.

  3. In digital ultrasound imaging, bit depth refers to:

    Answer: The number of bits used to encode the gray-scale value of each pixel

    Bit depth determines how many distinct gray levels can be represented; 8-bit depth yields 256 gray levels.

  4. Frame rate in real-time ultrasound imaging is primarily limited by:

    Answer: The speed of sound and imaging depth

    Because sound must travel to the maximum depth and return before the next pulse is fired, greater depth forces a lower pulse repetition frequency and thus a lower frame rate.

  5. What happens to frame rate when the number of scan lines per frame is increased while imaging depth remains constant?

    Answer: Frame rate decreases

    More scan lines require more pulses per frame, which increases the time needed to build each image and therefore reduces frame rate.

  6. The process of reducing high-amplitude speckle noise while preserving edge detail in ultrasound images is best described as:

    Answer: Adaptive image processing (speckle reduction imaging)

    Adaptive speckle reduction algorithms analyze local image statistics to smooth homogeneous regions while retaining boundaries.

  7. Which of the following correctly describes interpolation as used in the scan converter?

    Answer: Estimating pixel values between actual sample locations to fill the display grid

    Interpolation fills gaps between measured data points by estimating intermediate values, producing a continuous-looking image from discrete samples.