13.07: memory
Introduction to Memory in Ultrasound Systems
Overview:
The discussion centers around the memory circuits within ultrasound systems and their functions.
Memory is critical for storing echo signals and building images in ultrasound diagnostics.
Components of an Ultrasound System
Diagram of Ultrasound Components:
Previously covered components include:
Pulses
Power control
Transducer
Beam former including transmit focusing, receive focusing, apodization
Receiver Processes:
Involved processes:
Amplification
Compensation
Compression
Demodulation
Rejection
Function of Memory
Importance of Memory:
Stores amplitude and location of each echo signal received.
Each echo's location is assigned a specific address in memory where its amplitude is stored.
Memory facilitates the construction of ultrasound images by combining stored echoes.
Memory Structures:
Memory Matrix: An arrangement of address locations that store echo data.
Think of it like a checkerboard, where each square represents an address location.
Address Locations:
Store the echo amplitude at respective locations.
Each address location corresponds to a pixel in the displayed image.
Pixels = Picture Elements.
Types of Memory in Ultrasound
Historical Context:
Earlier systems referred to memory as scan converters converting vertical into horizontal information.
Digital Process:
Modern ultrasound systems utilize digital memory rather than analog.
Synonymous terms include "memory" and "digital scan converter."
Dimensions of Memory Matrix:
A matrix can be structured simply (e.g., 10x10) for illustrative purposes but is significantly larger in real applications.
Illustrative example: 10x10 = 100 pixels.
Storage of Echo Amplitudes in Memory
Example of Echo Storage:
For an echo with amplitude of 25 units stored in a specific address based on range.
Subsequent echoes (e.g., 37 microvolts, 14 units, and 32 units) follow the same pattern.
Illustrates how echoes are stored sequentially across multiple scan lines.
Sequential Scanning:
Each scan line contributes to building the full image.
Images consist of a series of address locations where echo amplitudes are recorded.
Matrix Size and Bit Depth
Matrix Size:
Essential for determining image resolution.
Typical ultrasound matrix sizes:
512x512 (roughly 250,000 total address locations)
1024x1024 (roughly 1 million pixels)
Bit Depth:
Defines how many values or shades of gray can be represented per pixel.
Example for typical ultrasound systems:
8 bits = 256 shades of gray.
More bits provide more shades and improve contrast resolution.
Bit Depth Examples
Shades of Gray Scenarios:
1 bit: 2 shades (black and white)
2 bits: 4 shades
3 bits: 8 shades
4 bits: 16 shades
5 bits: 32 shades
6 bits: 64 shades
7 bits: 128 shades
8 bits: 256 shades
9 bits: 512 shades
10 bits: 1024 shades
Digital Memory Characteristics
Total Bits Calculation:
Formula: Total Bits = Number of Pixels × Bit Depth
Example: For 1 million pixels and 8 bits per pixel = 8 million bits.
Memory Size in Bytes:
Conversion: Total Bits / 8 = Total Bytes.
Example: 8 million bits = 1 million bytes or 1 megabyte.
Important Digital Terminology
Bit:
Abbreviation for binary digit (0 or 1).
Byte:
A collection of 8 bits.
Kilobyte (KB):
Approx. 1024 bytes.
Megabyte (MB):
Approx. 1024 KB, or about 1 million bytes.
Gigabyte (GB):
Approx. 1024 MB, or about 1 billion bytes.
Terabyte (TB):
Approx. 1024 GB, or about 1 trillion bytes.
RAM vs. ROM:
RAM: Random Access Memory (Volatile)
ROM: Read-Only Memory (Non-volatile)
Practical Application and Implications
File Size for Ultrasound Images:
Single grayscale ultrasound images estimated to be around 1 MB. Often compressed for storage and retrieval.
Quality and Size Correlation:
Larger matrix sizes improve resolution but increase file size.
Increasing bit depth enhances contrast resolution but also increases file size.