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1/29/98 122 C95.3-1991 Revision — 2 nd Draft<br />

10/98 Draft<br />

reconstructed 3-dimensionally using Spyglass Slicer TM software on the PC <strong>and</strong><br />

VoxBlast TM software on the Silicon Graphics workstation to ensure correct anatomical<br />

placement of each tissue type. Each image was also checked <strong>for</strong> unknown pixel values<br />

using Wave Advantag eTM software. To predict SAR values, the anatomical in<strong>for</strong>mation<br />

within each TIF image file was converted to PGM files <strong>and</strong> imported into a FDTD<br />

mathematical model that used a look-up-table (LUT) containing permittivity values <strong>for</strong><br />

each tissue type.<br />

Development of models suitable <strong>for</strong> FDTD dosimetric calculations, while straight <strong>for</strong>ward,<br />

is not trivial. MRI <strong>and</strong> CT scans provide voxel maps of density, but many of the tissues<br />

have the same or similar densities, <strong>and</strong> many of the regions outside of the major organs<br />

require a detailed underst<strong>and</strong>ing of anatomy to determine what tissue are present, e.g.,<br />

fat, fluid, air. Even when some automatic tissue definition can be used, the bulk of the<br />

task falls on manual tissue recognition by a trained anatomist. Moreover, since FDTD<br />

calculations use the tissue dielectric properties, i.e., dielectric constant <strong>and</strong> conductivity,<br />

<strong>and</strong> mass density at each voxel location, knowledge of these properties <strong>for</strong><br />

Table D1 RGB colors <strong>for</strong> 42 tissue types<br />

Tissue Type RGB Value Tissue Type RGB Value<br />

Air (External) 9, 24, 135 Intestine (Large) 255, 0, 134<br />

Air (Internal) 0, 0, 0 Intestine (Small) 0, 255, 254<br />

Bile 105, 25, 132 Kidneys 180, 0, 255<br />

Bladder 0, 128, 0 Ligaments 50, 100, 200<br />

Blood 0, 255, 146 Liver 73, 0, 255<br />

Blood Vessel 200, 100, 200 Lung(Inner) 200, 112, 50<br />

Body Fluid 100, 255, 0 Lung (Outer) 0, 117, 255<br />

Bone (Cancellous) 170, 148, 12 Lymph 230, 99, 74<br />

Bone (Cortical) 255, 0, 217 Mucous Membrane 182, 255, 0<br />

Bone (Marrow) 128, 128, 128 Muscle 70. 255, 0<br />

Cartilage 255, 255, 128 Nails (Toe <strong>and</strong> Finger) 60, 200, 0<br />

Cerebral Spinal Fluid 208, 255, 0 Nerve (Spine) 0, 0, 255<br />

Eye (Cornea) 65, 63, 120 Nerve (Brain) 245, 150, 160<br />

Eye (Lens) 30, 50, 70 Pancreas 255, 0, 109<br />

Eye (Retina) 80, 100, 70 Skin/Dermis 255, 0, 0<br />

Eye (Sclera/Wall) 255, 220, 0 Spleen 255, 82, 0<br />

Eye (Aqueous Humor) 159, 0, 255 Stomach 140, 70, 20<br />

Fat 255, 112, 0 Testicles 113, 11, 11<br />

Gall Bladder 200, 60, 70 Tooth 10, 180, 80<br />

Gl<strong>and</strong>s 0, 87, 255 Perfect Conductor 150, 125, 0<br />

Heart 0, 128, 128 2/3 Muscle 180, 170, 160<br />

each voxel is also required. Properties of many of the tissues has been measured over a<br />

wide frequency range [Gabriel, 1996; Stuchly <strong>and</strong> Stuchly, 1980; Geddes <strong>and</strong> Baker,<br />

1967; Durney, et al., 1986]. All tissues are highly frequency dispersive, <strong>and</strong> some<br />

tissues, e.g., bone, heart, skeletal muscle, demonstrate anisotropic properties at<br />

frequencies below 1 MHz [Epstein <strong>and</strong> Foster, 1983]. Additional measurements of tissue<br />

properties are on-going as there remains questions about variations in tissue properties<br />

with individuals, age, health status, temperature, in vivo versus in vitro, etc.<br />

Copyright © 1998 IEEE. All rights reserved. This is an unapproved IEEE St<strong>and</strong>ards Draft,<br />

subject to change.

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