Базовый коммит

2025-12-03 16:50:06 +05:00
commit 939932eeb0
38 changed files with 2942 additions and 0 deletions
@@ -0,0 +1,86 @@
+from typing import NamedTuple
+import os
+import torch
+import numpy as np
+import pydicom
+from service.structs import PredictorInput, TagError, MetaTags
+
+
+class InputImage(NamedTuple):
+    img: np.ndarray
+    ww: int
+    wc: int
+    uid: str
+    color_inversion: bool
+
+
+def _get_ww_wc(study_ww, study_wc):
+    if type(study_ww) is pydicom.valuerep.DSfloat:
+        return int(study_ww), int(study_wc)
+    return int(study_ww[0]), int(study_wc[0])
+
+
+def _is_color_inverted(study):
+    return study.PhotometricInterpretation == "MONOCHROME1"
+
+
+def _prep_img(img_pack: InputImage) -> torch.Tensor:
+    img = img_pack.img.astype(np.float32)
+    lower_bound = img_pack.wc - 0.5 * img_pack.ww
+    upper_bound = img_pack.wc + 0.5 * img_pack.ww
+    img = np.clip(img, lower_bound, upper_bound)
+    img = ((img - lower_bound) / img_pack.ww) * 255
+    img = img.astype(np.uint8)
+    if img_pack.color_inversion:
+        img = 255 - img
+    return torch.from_numpy(img[None, ...])
+
+
+def _check_required_tags(study: pydicom.FileDataset, pathology: str):
+    invalid_tags = []
+    if not (hasattr(study, "PhotometricInterpretation") and 
+            study.PhotometricInterpretation in ("MONOCHROME1", "MONOCHROME2")):
+        invalid_tags.append("PhotometricInterpretation")
+    if pathology in ("shoulder", "wrist"):
+        if not (hasattr(study, "PixelSpacing") or
+                hasattr(study, "ImagerPixelSpacing")):
+            invalid_tags.append("PixelSpacing/ImagerPixelSpacing")
+    for tag in ("WindowWidth", "WindowCenter"):
+        if not hasattr(study, tag) or getattr(study, tag) == "":
+            invalid_tags.append(tag)
+    if len(invalid_tags) == 1:
+        raise TagError(f"DICOM тег {invalid_tags[0]} не заполнен, "\
+                       "либо имеет некорректное значение")
+    elif len(invalid_tags) > 1:
+        raise TagError(f"DICOM теги {", ".join(invalid_tags)} не заполнены, "\
+                       "либо имеют некорректные значения")
+
+
+def _get_meta_tags(study: pydicom.FileDataset):
+    return MetaTags(study.StudyInstanceUID, study.SeriesInstanceUID,
+                    getattr(study, "PatientID", None), 
+                    getattr(study, "AccessionNumber", None),
+                    getattr(study, "IssuerOfPatientID", None),
+                    getattr(study, "FillerOrderNumberImagingServiceRequest",
+                                    None))
+
+
+def _get_px_size(study: pydicom.FileDataset):
+    if hasattr(study, "PixelSpacing"):
+        return study.PixelSpacing
+    if hasattr(study, "ImagerPixelSpacing"):
+        return study.ImagerPixelSpacing
+    return None, None
+
+
+def prep_imgs(pathology: str, study_path: str) -> tuple[MetaTags, PredictorInput]:
+    instance = pydicom.dcmread(study_path, force=True)
+    _check_required_tags(instance, pathology)
+    meta_tags = _get_meta_tags(instance)
+    ww, wc = _get_ww_wc(instance.WindowWidth, instance.WindowCenter)
+    clr_inverted = _is_color_inverted(instance)
+    img = InputImage(instance.pixel_array, ww, wc, meta_tags.study_iuid, clr_inverted)
+    pred_input = PredictorInput(meta_tags.study_iuid, _prep_img(img),
+                                getattr(instance, "ImageLaterality", None),
+                                *_get_px_size(instance))
+    return meta_tags, pred_input