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3e09c97 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 | # 104 Anatomical Structure Labels for TotalSegmentator / MONAI wholeBody_ct_segmentation
# Based on TotalSegmentator v1 class definitions
LABEL_NAMES = {
0: "background",
1: "spleen",
2: "kidney_right",
3: "kidney_left",
4: "gallbladder",
5: "liver",
6: "stomach",
7: "aorta",
8: "inferior_vena_cava",
9: "portal_vein_and_splenic_vein",
10: "pancreas",
11: "adrenal_gland_right",
12: "adrenal_gland_left",
13: "lung_upper_lobe_left",
14: "lung_lower_lobe_left",
15: "lung_upper_lobe_right",
16: "lung_middle_lobe_right",
17: "lung_lower_lobe_right",
18: "vertebrae_L5",
19: "vertebrae_L4",
20: "vertebrae_L3",
21: "vertebrae_L2",
22: "vertebrae_L1",
23: "vertebrae_T12",
24: "vertebrae_T11",
25: "vertebrae_T10",
26: "vertebrae_T9",
27: "vertebrae_T8",
28: "vertebrae_T7",
29: "vertebrae_T6",
30: "vertebrae_T5",
31: "vertebrae_T4",
32: "vertebrae_T3",
33: "vertebrae_T2",
34: "vertebrae_T1",
35: "vertebrae_C7",
36: "vertebrae_C6",
37: "vertebrae_C5",
38: "vertebrae_C4",
39: "vertebrae_C3",
40: "vertebrae_C2",
41: "vertebrae_C1",
42: "esophagus",
43: "trachea",
44: "heart_myocardium",
45: "heart_atrium_left",
46: "heart_ventricle_left",
47: "heart_atrium_right",
48: "heart_ventricle_right",
49: "pulmonary_artery",
50: "brain",
51: "iliac_artery_left",
52: "iliac_artery_right",
53: "iliac_vena_left",
54: "iliac_vena_right",
55: "small_bowel",
56: "duodenum",
57: "colon",
58: "rib_left_1",
59: "rib_left_2",
60: "rib_left_3",
61: "rib_left_4",
62: "rib_left_5",
63: "rib_left_6",
64: "rib_left_7",
65: "rib_left_8",
66: "rib_left_9",
67: "rib_left_10",
68: "rib_left_11",
69: "rib_left_12",
70: "rib_right_1",
71: "rib_right_2",
72: "rib_right_3",
73: "rib_right_4",
74: "rib_right_5",
75: "rib_right_6",
76: "rib_right_7",
77: "rib_right_8",
78: "rib_right_9",
79: "rib_right_10",
80: "rib_right_11",
81: "rib_right_12",
82: "humerus_left",
83: "humerus_right",
84: "scapula_left",
85: "scapula_right",
86: "clavicula_left",
87: "clavicula_right",
88: "femur_left",
89: "femur_right",
90: "hip_left",
91: "hip_right",
92: "sacrum",
93: "face",
94: "gluteus_maximus_left",
95: "gluteus_maximus_right",
96: "gluteus_medius_left",
97: "gluteus_medius_right",
98: "gluteus_minimus_left",
99: "gluteus_minimus_right",
100: "autochthon_left",
101: "autochthon_right",
102: "iliopsoas_left",
103: "iliopsoas_right",
104: "urinary_bladder",
}
# Color map for visualization (RGB values)
# Using a custom colormap for better visualization
import numpy as np
def get_color_map():
"""Generate a color map for 105 classes (background + 104 structures)"""
np.random.seed(42) # For reproducibility
colors = np.zeros((105, 3), dtype=np.uint8)
# Background is black
colors[0] = [0, 0, 0]
# Assign distinct colors to different organ categories
# Organs (1-12): Warm colors
organ_colors = [
[255, 99, 71], # spleen - tomato
[255, 165, 0], # kidney_right - orange
[255, 140, 0], # kidney_left - dark orange
[50, 205, 50], # gallbladder - lime green
[139, 69, 19], # liver - saddle brown
[255, 192, 203], # stomach - pink
[220, 20, 60], # aorta - crimson
[0, 0, 139], # inferior_vena_cava - dark blue
[138, 43, 226], # portal_vein_and_splenic_vein - blue violet
[255, 215, 0], # pancreas - gold
[255, 255, 0], # adrenal_gland_right - yellow
[255, 255, 0], # adrenal_gland_left - yellow
]
colors[1:13] = organ_colors
# Lungs (13-17): Light blue shades
colors[13:18] = [[135, 206, 235], [100, 149, 237], [30, 144, 255], [0, 191, 255], [70, 130, 180]]
# Vertebrae (18-41): Gradient from red to purple
for i in range(18, 42):
colors[i] = [200 - (i-18)*5, 100, 150 + (i-18)*3]
# Other structures (42-57): Various colors
colors[42] = [255, 182, 193] # esophagus
colors[43] = [176, 224, 230] # trachea
colors[44:49] = [[220, 20, 60], [255, 105, 180], [255, 20, 147], [255, 182, 193], [199, 21, 133]] # heart
colors[49] = [148, 0, 211] # pulmonary_artery
colors[50] = [255, 218, 185] # brain
colors[51:55] = [[178, 34, 34], [178, 34, 34], [70, 130, 180], [70, 130, 180]] # iliac vessels
colors[55:58] = [[222, 184, 135], [210, 180, 140], [188, 143, 143]] # bowels
# Ribs (58-81): Bone color variations
for i in range(58, 82):
colors[i] = [255, 250, 205 + (i-58) % 50]
# Bones (82-92): Gray/white shades
for i in range(82, 93):
colors[i] = [220 + (i-82)*2, 220 + (i-82)*2, 220]
# Face and muscles (93-103): Skin and muscle tones
colors[93] = [255, 228, 196] # face
for i in range(94, 104):
colors[i] = [205, 92, 92 + (i-94)*5] # muscles - indian red variations
# Bladder
colors[104] = [255, 255, 0] # urinary_bladder - yellow
return colors
def get_label_name(label_id: int) -> str:
"""Get human-readable name for a label ID"""
return LABEL_NAMES.get(label_id, f"unknown_{label_id}").replace("_", " ").title()
def get_organ_categories():
"""Group organs by category for UI display"""
return {
"Major Organs": [1, 2, 3, 4, 5, 6, 10, 104],
"Cardiovascular": [7, 8, 9, 44, 45, 46, 47, 48, 49, 51, 52, 53, 54],
"Respiratory": [13, 14, 15, 16, 17, 43],
"Digestive": [42, 55, 56, 57],
"Vertebrae": list(range(18, 42)),
"Ribs": list(range(58, 82)),
"Upper Body Bones": [82, 83, 84, 85, 86, 87],
"Lower Body Bones": [88, 89, 90, 91, 92],
"Muscles": list(range(94, 104)),
"Other": [11, 12, 50, 93],
}
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