解剖学的グループの可視化

注釈

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解剖学的グループの可視化#

This example visualizes different anatomical groups using the segmentation labels available from the downloadable datasets download_whole_body_ct_female() and download_whole_body_ct_male().

These datasets include labels for 117 anatomical structures. In this example, the labels are grouped by filtering the list of labels and coloring the labels with the recommended RGB values used by the 3DSlicer TotalSegmentator Extension.

from __future__ import annotations

import pyvista as pv
from pyvista import examples

データセットのロード#

TotalSegmentator データセットを読み込みます。 male または female PyVista に含まれる女性被験者、または TotalSegmentator dataset に含まれるその他の被験者。

dataset = examples.download_whole_body_ct_female()

異なる解剖学的グループのプロットに使用されるラベルマップを取得します。

label_map = dataset['label_map']

データセットに関連するメタデータを取得します

# Get a list of all label names. This list will be filtered by group.
label_names = dataset['segmentations'].keys()

# Get color and id mappings included with the dataset. These are used to filter and
# color the contours.
names_to_colors = dataset.user_dict['names_to_colors']
names_to_ids = dataset.user_dict['names_to_ids']
ids_to_colors = dataset.user_dict['ids_to_colors']

カラーマッピング#

データセットに含まれるカラーマッピングを表示します。 辞書を印刷し、RGB値を視覚的に揃えるようにフォーマットします。 フォーマットされた辞書は有効なpythonコードです。

print('{')
for name, (R, G, B) in names_to_colors.items():
    print(f'{name!r:<32}: ({R:>3}, {G:>3}, {B:>3}),')
print('}')

{
'adrenal_gland_left'            : (249, 186, 150),
'adrenal_gland_right'           : (249, 186, 150),
'aorta'                         : (224,  97,  76),
'atrial_appendage_left'         : (  0, 161, 196),
'autochthon_left'               : (171,  85,  68),
'autochthon_right'              : (171,  85,  68),
'brachiocephalic_trunk'         : (196, 121,  79),
'brachiocephalic_vein_left'     : (  0, 161, 196),
'brachiocephalic_vein_right'    : (  0, 151, 206),
'brain'                         : (250, 250, 225),
'clavicula_left'                : (205, 179, 108),
'clavicula_right'               : (205, 179, 108),
'colon'                         : (204, 168, 143),
'common_carotid_artery_left'    : (  0, 112, 165),
'common_carotid_artery_right'   : ( 10, 105, 155),
'costal_cartilages'             : (111, 184, 210),
'duodenum'                      : (255, 253, 229),
'esophagus'                     : (211, 171, 143),
'femur_left'                    : (255, 238, 170),
'femur_right'                   : (255, 238, 170),
'gallbladder'                   : (139, 150,  98),
'gluteus_maximus_left'          : (188,  95,  76),
'gluteus_maximus_right'         : (188,  95,  76),
'gluteus_medius_left'           : (178, 105,  76),
'gluteus_medius_right'          : (178, 105,  76),
'gluteus_minimus_left'          : (178,  95,  86),
'gluteus_minimus_right'         : (178,  95,  86),
'heart'                         : (206, 110,  84),
'hip_left'                      : (212, 188, 102),
'hip_right'                     : (212, 188, 102),
'humerus_left'                  : (205, 179, 108),
'humerus_right'                 : (205, 179, 108),
'iliac_artery_left'             : (216, 101,  79),
'iliac_artery_right'            : (216, 101,  79),
'iliac_vena_left'               : (  0, 151, 206),
'iliac_vena_right'              : (  0, 151, 206),
'iliopsoas_left'                : (188,  95,  76),
'iliopsoas_right'               : (188,  95,  76),
'inferior_vena_cava'            : (  0, 151, 206),
'kidney_cyst_left'              : (205, 205, 100),
'kidney_cyst_right'             : (205, 205, 100),
'kidney_left'                   : (185, 102,  83),
'kidney_right'                  : (185, 102,  83),
'liver'                         : (221, 130, 101),
'lung_lower_lobe_left'          : (224, 186, 162),
'lung_lower_lobe_right'         : (224, 186, 162),
'lung_middle_lobe_right'        : (202, 164, 140),
'lung_upper_lobe_left'          : (172, 138, 115),
'lung_upper_lobe_right'         : (172, 138, 115),
'pancreas'                      : (249, 180, 111),
'portal_vein_and_splenic_vein'  : (  0, 151, 206),
'prostate'                      : (230, 158, 140),
'pulmonary_vein'                : (  0, 122, 171),
'rib_left_1'                    : (253, 232, 158),
'rib_left_10'                   : (253, 232, 158),
'rib_left_11'                   : (253, 232, 158),
'rib_left_12'                   : (253, 232, 158),
'rib_left_2'                    : (253, 232, 158),
'rib_left_3'                    : (253, 232, 158),
'rib_left_4'                    : (253, 232, 158),
'rib_left_5'                    : (253, 232, 158),
'rib_left_6'                    : (253, 232, 158),
'rib_left_7'                    : (253, 232, 158),
'rib_left_8'                    : (253, 232, 158),
'rib_left_9'                    : (253, 232, 158),
'rib_right_1'                   : (253, 232, 158),
'rib_right_10'                  : (253, 232, 158),
'rib_right_11'                  : (253, 232, 158),
'rib_right_12'                  : (253, 232, 158),
'rib_right_2'                   : (253, 232, 158),
'rib_right_3'                   : (253, 232, 158),
'rib_right_4'                   : (253, 232, 158),
'rib_right_5'                   : (253, 232, 158),
'rib_right_6'                   : (253, 232, 158),
'rib_right_7'                   : (253, 232, 158),
'rib_right_8'                   : (253, 232, 158),
'rib_right_9'                   : (253, 232, 158),
'sacrum'                        : (212, 188, 102),
'scapula_left'                  : (212, 188, 102),
'scapula_right'                 : (212, 188, 102),
'skull'                         : (241, 213, 144),
'small_bowel'                   : (205, 167, 142),
'spinal_cord'                   : (244, 214,  49),
'spleen'                        : (157, 108, 162),
'sternum'                       : (244, 217, 154),
'stomach'                       : (216, 132, 105),
'subclavian_artery_left'        : (216, 101,  69),
'subclavian_artery_right'       : (216, 101,  89),
'superior_vena_cava'            : (  0, 141, 226),
'thyroid_gland'                 : (220, 160,  30),
'trachea'                       : (182, 228, 255),
'urinary_bladder'               : (222, 154, 132),
'vertebrae_C1'                  : (255, 255, 207),
'vertebrae_C2'                  : (255, 255, 207),
'vertebrae_C3'                  : (255, 255, 207),
'vertebrae_C4'                  : (255, 255, 207),
'vertebrae_C5'                  : (255, 255, 207),
'vertebrae_C6'                  : (255, 255, 207),
'vertebrae_C7'                  : (255, 255, 207),
'vertebrae_L1'                  : (212, 188, 102),
'vertebrae_L2'                  : (212, 188, 102),
'vertebrae_L3'                  : (212, 188, 102),
'vertebrae_L4'                  : (212, 188, 102),
'vertebrae_L5'                  : (212, 188, 102),
'vertebrae_S1'                  : (212, 208, 122),
'vertebrae_T1'                  : (226, 202, 134),
'vertebrae_T10'                 : (226, 202, 134),
'vertebrae_T11'                 : (226, 202, 134),
'vertebrae_T12'                 : (226, 202, 134),
'vertebrae_T2'                  : (226, 202, 134),
'vertebrae_T3'                  : (226, 202, 134),
'vertebrae_T4'                  : (226, 202, 134),
'vertebrae_T5'                  : (226, 202, 134),
'vertebrae_T6'                  : (226, 202, 134),
'vertebrae_T7'                  : (226, 202, 134),
'vertebrae_T8'                  : (226, 202, 134),
'vertebrae_T9'                  : (226, 202, 134),
}

ユーティリティ関数#

データを視覚化するヘルパー関数を定義します。

filter_labels#

特定の解剖学的領域のグループを視覚化するために、まず、名前によってラベルをフィルタリングする関数を定義します。 用語のリストが与えられると、この関数は検索用語のいずれかを含むラベルを返します。

def filter_labels(label_names: list[str], search_terms: list[str]):
    def include_label(label_name: str):
        return any(target in label_name for target in search_terms)

    return [label for label in label_names if include_label(label)]

plot_anatomy#

用語のリストが与えられると、それらの用語に関連するラベルを検索し、ラベルに対応する等高線を生成し、結果をプロットする関数を定義します。 この関数は等高線の生成に contour_labels() を使用し、色付けに color_labels() を使用します。

def plot_anatomy(search_terms: list[str]):
    # Get a list of labels which contain any of the listed terms.
    group_names = filter_labels(label_names, search_terms)

    # Get the label ids corresponding to the matched labels.
    group_ids = [names_to_ids[name] for name in group_names]

    # Selectively generate surfaces for the specified labels
    group_surface = dataset['label_map'].contour_labels(select_inputs=group_ids)

    # Color the labels with the color mapping
    colored_surface = group_surface.color_labels(colors=ids_to_colors)

    # Plot the label map.
    pl = pv.Plotter()
    pl.add_mesh(colored_surface)
    pl.view_zx()
    pl.camera.up = (0, 0, 1)
    pl.show()

解剖学的グループ#

ラベルをグループ化し、結果を視覚化します。

心臓血管系#

循環器系のセグメントを表示します。

# Define terms which describe all relevant segments.
cardio = [
    'heart',
    'aorta',
    'artery',
    'brachiocephalic_trunk',
    'vein',
    'atrial_appendage',
    'vena_cava',
]

# Plot the labels associated with these terms.
plot_anatomy(cardio)
anatomical groups

消化器系#

消化器系のセグメントを表示します。

# Define terms which describe all relevant segments.
gastro = [
    'esophagus',
    'stomach',
    'duodenum',
    'small_bowel',
    'colon',
    'urinary_bladder',
]

# Plot the labels associated with these terms.
plot_anatomy(gastro)
anatomical groups

背骨#

背骨のセグメントを表示します。

# Define terms which describe all relevant segments.
spine = [
    'spinal_cord',
    'vertebrae',
    'sacrum',
]

# Plot the labels associated with these terms.
plot_anatomy(spine)
anatomical groups

その他の臓器#

Show other organs not included in the cardiovascular or gastrointestinal systems.

# Define terms which describe all relevant segments.
other_organs = [
    'brain',
    'spinal_cord',
    'thyroid_gland',
    'trachea',
    'lung',
    'adrenal_gland',
    'spleen',
    'liver',
    'gallbladder',
    'kidney',
    'pancreas',
    'prostate',
]

# Plot the labels associated with these terms.
plot_anatomy(other_organs)
anatomical groups

筋肉#

筋肉を表示します．

# Define terms which describe all relevant segments.
muscles = [
    'gluteus',
    'autochthon',
    'iliopsoas',
]

# Plot the labels associated with these terms.
plot_anatomy(muscles)
anatomical groups

肋骨#

肋骨を表示します．

# Define terms which describe all relevant segments.
ribs = [
    'rib',
    'sternum',
    'costal_cartilages',
]

# Plot the labels associated with these terms.
plot_anatomy(ribs)
anatomical groups

骨格#

骨格を表示します．

# Define terms which describe all relevant segments.
skeleton = [
    'skull',
    'clavicula',
    'scapula',
    'humerus',
    'vertebrae',
    'sternum',
    'rib',
    'costal_cartilages',
    'hip',
    'sacrum',
    'femur',
]

# Plot the labels associated with these terms.
plot_anatomy(skeleton)
anatomical groups

Tags: medical

Total running time of the script: (0 minutes 11.515 seconds)

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