#!/home/xfr/.conda/envs/cbt/bin/python """把 PSO 找到的 CBT 螺絲位置(旋轉 0.5mm 標準系)映回原始 (未旋轉、未重取樣)native CT 空間,整支 volume 各 level 的螺絲 (L1-L5 x L/R,最多 10 支)存成單一 label 體積: Output_dir///cbt.nii.gz Output_dir///x-ap.jpg 合成前後(AP) X 光投影视圖 Output_dir///x-lat.jpg 合成側位 X 光投影视圖 (只投影脊椎骨 + 螺絲、不含軟組織; 見 render_xray_projections) label 值:L1L=1 L1R=2 L2L=3 L2R=4 L3L=5 L3R=6 L4L=7 L4R=8 L5L=9 L5R=10 (0 = 背景)。 座標鏈首選:直接用預處理寫檔時記錄在 /transform.json 的正向鏈 (imaging.transforms.original_to_source:boxes / std_flip_axes / ap_flip / rotated R、center、start / 原 CT 幾何;純 index 空間、不依賴 standardized 輸出的物理 header)。該鏈為仿射(original index <-> rotated disk index), 螺絲點經仿射逆向 o = M^-1 (s - t) 精確映射——不重新估算任何平面 / 幾何、 不重取樣 native label。 fallback(僅舊世代 volume 沒有 transform.json、或該 level 沒有 rotated 記錄時):純 index 空間重算 R/center(template 骨頭 mask 的 best_symmetry_plane / best_upper_endplate_plane)、fstart(rotated 檔 origin 反映到 template index 的整數)、bbox2(native label 0.5mm 線性 重取樣 >0.5 的最大 26-連通區域 bbox): rotated disk r -> t = R^T (r + fstart - c) + c -> g0 = bbox2s + (wx-1-tx, wy-1-ty, tz);ap_flip 時 g0y = N05y-1-g0y -> native: rint(g0 * 0.5 / sn) 重算結果可能與生成時參數不完全一致:2026-09-09 驗證 liver_100 螺絲柱 in-label 由 93-99%(transform.json)掉到 30-94%(重算);新世代資料 (transform.json 在)一律走主路徑。 螺絲參數化(rotated 系、0.5mm index):pos = [z, y, x, az°, alt°, d mm, L mm]; 方向 d_v = (cos az sin alt, sin az sin alt, cos alt);末端 = p0 + L/0.5 * d_v; 柱半徑 = d/2 mm。 驗證(2026-09-09,transform.json 路徑):20260909_141448 run — 0001(10/10)、liver_100(10/10)、covid19(L1/L2 六側)螺絲柱體 in-label >= 92%、2-voxel 膨脹 >= 98%。covid19 L3 兩側除外:該 volume 的 L3 旋轉 bone mask 是 4.5k voxel / 5 slice 的退化區域(L4/L5 預處理缺檔、 先前棘突切除),屬資料問題非映射問題(L3 bone 碎片本身逆向 in-label 97.8%)。 """ import argparse import json import logging import os import sys import numpy as np import SimpleITK as sitk from tinydb import TinyDB, Query from config.constant import LABEL_MAP from imaging.resample import resample_img from imaging.segmentation import _largest_cc_bbox from imaging.orientation import best_symmetry_plane, best_upper_endplate_plane from imaging.transforms import (level_file_path, load_transform, original_to_source, transform_path) from visualization.res_bone_figure import compute_normalizing_rotation standardized_dir = '/mnt/1248/open2/cyrou/CBT/Seg/Resample/standardized-xfr-3' data_root = '/mnt/1220/Public/dataset/Spine/CTSpine1K/data/' label_root = '/mnt/1220/Public/dataset/Spine/CTSpine1K/label/' SUBDIRS = { 'colon': 'conlon', 'COVID-19': 'COVID-19', 'HNSCC-3DCT-RT_neck': 'HNSCC-3DCT-RT_neck', 'liver': 'Liver', } Output_dir = '/mnt/1248/open/cyrou/Output' _PROJ_DIR = os.path.dirname(os.path.abspath(__file__)) LOG_DIR = os.path.join(_PROJ_DIR, 'logs') SIDE_RESULT_DIR = os.path.join(LOG_DIR, 'side_results') META_DB = os.path.join(_PROJ_DIR, 'xfr_image_metadata.json') LEVELS = ('L1', 'L2', 'L3', 'L4', 'L5') LEVEL_LABEL_VAL = {v: int(k) for k, v in LABEL_MAP.items() if v in LEVELS} # {'L1': 20, ...} PROJ_FILENAME = {'ap': 'x-ap.jpg', 'lateral': 'x-lat.jpg'} logger = logging.getLogger('xfr_cbt_native') def find_native_paths(volume_id): """回傳 (ct_path, label_path, ap_flip);找不到 native 檔對時 raise。""" ap_flip = False try: meta = TinyDB(META_DB, access_mode='r').table('images') \ .get(Query().name == volume_id) if meta is None: logger.warning(f'{volume_id}: not in metadata db; ap_flip defaults to False') else: ap_flip = bool(meta.get('ap_flip', False)) except Exception as e: logger.warning(f'{volume_id}: metadata db unavailable ({e}); ap_flip defaults to False') for sub, lab_sub in SUBDIRS.items(): ct = f'{data_root}{sub}/{volume_id}.nii.gz' lb = f'{label_root}{lab_sub}/{volume_id}_seg.nii.gz' if os.path.isfile(ct) and os.path.isfile(lb): return ct, lb, ap_flip raise FileNotFoundError(f'{volume_id}: no native CT/label pair under {data_root}') def level_geometry(volume_id, level, lb_img, lb_arr): """每 level 的 (R, c, fstart, bbox2s, wx, wy);與預處理/驗證腳本同定義。""" vol_dir = os.path.join(standardized_dir, volume_id) # 未旋轉檔:新世代在 crop/ 子資料夾、舊世代在頂層 smd_img = sitk.ReadImage(level_file_path(vol_dir, level, 'smd_resampled')) smd = sitk.GetArrayFromImage(smd_img).astype(np.float32) if not (np.isfinite(smd).all() and smd.min() < 0 and smd.max() > 0): b = (sitk.GetArrayFromImage( sitk.ReadImage(level_file_path(vol_dir, level, 'binary_nn'))) > 0).astype(np.uint8) else: b = (smd < 0.5).astype(np.uint8) sym = best_symmetry_plane(b) symp = best_upper_endplate_plane(b) R, c = compute_normalizing_rotation(b, sym, symp) rot_img = sitk.ReadImage(f'{vol_dir}/rotated/{level}_binary_sdf.nii.gz') fstart = np.round(np.array( smd_img.TransformPhysicalPointToIndex(rot_img.GetOrigin()))).astype(float) lv = LEVEL_LABEL_VAL[level] bin_img = sitk.GetImageFromArray((lb_arr == lv).astype(np.uint8)) bin_img.CopyInformation(lb_img) bin_lin = resample_img(sitk.Cast(bin_img, sitk.sitkFloat32)) m_full = sitk.GetImageFromArray((sitk.GetArrayFromImage(bin_lin) > 0.5).astype(np.uint8)) m_full.CopyInformation(bin_lin) cc = _largest_cc_bbox(m_full) if cc is None: raise ValueError(f'{volume_id} {level}: empty native level mask (label {lv})') _, bbox2 = cc wx, wy = smd_img.GetSize()[0], smd_img.GetSize()[1] return R, c, fstart, np.array(bbox2[:3], float), wx, wy def rotated_to_native(r_xyz, geom, N05, sn, ap_flip): """r_xyz: (N,3) rotated disk (x,y,z) index -> (N,3) native 連續 index。""" R, c, fstart, bbox2s, wx, wy = geom t = (np.asarray(r_xyz, float) + fstart - c) @ R + c g0 = np.empty_like(t) g0[:, 0] = bbox2s[0] + (wx - 1 - t[:, 0]) g0[:, 1] = bbox2s[1] + (wy - 1 - t[:, 1]) g0[:, 2] = bbox2s[2] + t[:, 2] if ap_flip: g0[:, 1] = N05[1] - 1 - g0[:, 1] return g0 * (0.5 / sn) def screw_voxel_xyz(pos): """pos = [z, y, x, az°, alt°, d, L](rotated 系 0.5mm index)。 回傳柱體內 (x,y,z) float voxel 座標(N,3)。""" z, y, x, az, alt, d, L = (float(v) for v in pos[:7]) azr, altr = np.radians(az), np.radians(alt) ca, sa = np.cos(azr), np.sin(azr) ct_, st_ = np.cos(altr), np.sin(altr) dv = np.array([ca * st_, sa * st_, ct_]) e1 = np.array([ca * ct_, sa * ct_, -st_]) e2 = np.array([-sa, ca, 0.0]) p0 = np.array([x, y, z]) p1 = p0 + (L / 0.5) * dv rad = d / 0.5 + 3.0 lo = np.floor(np.minimum(p0, p1)) - rad hi = np.ceil(np.maximum(p0, p1)) + rad xs, ys, zs = np.meshgrid(np.arange(lo[0], hi[0] + 1), np.arange(lo[1], hi[1] + 1), np.arange(lo[2], hi[2] + 1), indexing='xy') P = np.stack([xs.ravel(), ys.ravel(), zs.ravel()], 1) dP = P - p0 xr, yr, zr = dP @ e1, dP @ e2, dP @ dv rrad = d # (d/2 mm 半徑) / 0.5mm 每 voxel = d 個 voxel m = (xr ** 2 + yr ** 2 <= rrad ** 2) & (zr >= 0) & (zr <= L / 0.5) return P[m] def write_volume_cbt(volume_id, run_id, output_root=Output_dir, date=None): """把一個 volume 的 side_results 螺絲全部映回 native 空間寫 cbt.nii.gz。 回傳 (path, n_screws);該 run 無此 volume 時回傳 (None, 0)。""" date = date or run_id[:8] side_vol_dir = os.path.join(SIDE_RESULT_DIR, run_id, volume_id) if not os.path.isdir(side_vol_dir): logger.warning(f'{volume_id}: no side results under {side_vol_dir}; cbt skipped') return None, 0 if not any(os.path.isfile(os.path.join(side_vol_dir, f'{l}_{s}.json')) for l in LEVELS for s in ('L', 'R')): logger.warning(f'{volume_id}: no _.json in {side_vol_dir}; cbt skipped') return None, 0 ct_path, lb_path, ap_flip = find_native_paths(volume_id) ct = sitk.ReadImage(ct_path) n_xyz = np.array(ct.GetSize(), int) # (x,y,z) n_zyx = n_xyz[::-1].copy() # 輸出 (z,y,x) sn = np.array(ct.GetSpacing(), float) N05 = np.maximum(1, np.ceil(n_xyz.astype(float) * sn / 0.5 - 1e-6).astype(int)) # 主路徑:transform.json 記錄的正向鏈(仿射),逆向 o = M^-1 (s - t) meta = None try: meta = load_transform(os.path.join(standardized_dir, volume_id)) except FileNotFoundError: logger.warning(f'{volume_id}: no transform.json ' f'({transform_path(os.path.join(standardized_dir, volume_id))}); ' f'全部 level 退回重算路徑(近似)') if meta is not None and not np.array_equal( np.asarray(meta['original']['size'], int), n_xyz): logger.warning(f'{volume_id}: transform.json original size ' f'{meta["original"]["size"]} != CT {list(n_xyz)}; ' f'忽略 transform.json,退回重算路徑') meta = None out_arr = np.zeros(n_zyx, np.uint8) lb_img = lb_arr = None # fallback 才需要讀 native label geom_cache = {} # fallback:每 level 的 (R, c, fstart, bbox2s, wx, wy) aff_cache = {} # 主路徑:每 level 的 (M^-1, t) n_screws, skipped = 0, [] n_tf = n_fb = 0 for li, level in enumerate(LEVELS): for side in ('L', 'R'): jp = os.path.join(side_vol_dir, f'{level}_{side}.json') if not os.path.isfile(jp): continue pos = json.load(open(jp))['position'] try: cyl = screw_voxel_xyz(pos) lv = meta['levels'].get(level) if meta is not None else None if lv is not None and 'rotated' in lv: if level not in aff_cache: M, t = original_to_source(meta, level, 'rotated') aff_cache[level] = (np.linalg.inv(M), t) Mi, t = aff_cache[level] nat = (cyl - t) @ Mi.T # (N,3) 原 CT 連續 index n_tf += 1 else: if lb_arr is None: lb_img = sitk.ReadImage(lb_path) lb_arr = sitk.GetArrayFromImage(lb_img) if level not in geom_cache: geom_cache[level] = level_geometry(volume_id, level, lb_img, lb_arr) nat = rotated_to_native(cyl, geom_cache[level], N05, sn, ap_flip) n_fb += 1 ni = np.rint(nat).astype(int) valid = (ni >= 0).all(1) & (ni < n_xyz).all(1) idx = ni[valid] if idx.shape[0] == 0: raise ValueError('all screw voxels out of original CT bounds') val = li * 2 + 1 + (1 if side == 'R' else 0) out_arr[idx[:, 2], idx[:, 1], idx[:, 0]] = val n_screws += 1 except Exception as e: logger.error(f'{volume_id} {level}_{side}: {e}') skipped.append(f'{level}_{side} ({e})') if n_screws == 0: raise ValueError(f'{volume_id}: no screw could be written (skipped: {skipped or "none read"})') out_dir = os.path.join(output_root, date, volume_id) os.makedirs(out_dir, exist_ok=True) out_img = sitk.GetImageFromArray(out_arr) out_img.CopyInformation(ct) out_path = os.path.join(out_dir, 'cbt.nii.gz') sitk.WriteImage(out_img, out_path) if skipped: logger.warning(f'{volume_id}: failed sides: {", ".join(skipped)}') logger.info(f'{volume_id}: {n_screws}/10 screws -> {out_path} ' f'(transform.json={n_tf}, re-est={n_fb}, ap_flip={ap_flip})') # 收尾:原 CT + 螺絲 -> 合成 AP / Lateral X 光投影视圖 (x-ap.jpg / x-lat.jpg) try: render_xray_projections(out_path, ct_path, out_dir) except Exception as e: logger.warning(f'{volume_id}: X-ray projection render failed: {e}') return out_path, n_screws def render_xray_projections(cbt_path, ct_path, out_dir, views=('ap', 'lateral'), margin_mm=50.0): """原 CT + cbt.nii.gz(native 同一 grid 的螺絲 label)-> 合成「只有骨頭」X 光投影视圖。 只投影脊椎骨 + 螺絲,不含軟組織: - spine mask:native 分割 label(1-24 = C1..L5,見 config.constant.LABEL_MAP); label 缺 / grid 不符時退回 HU 300-3000 閾值。 - 骨 μ = clip(HU, 0, 2000)/400(松質骨~0.2-1、皮質/終板~2-5)。 - 螺絲 voxel μ = 60(金屬等效,最亮白)。 投影视圖 = 沿中心射線 μ 的線積分(AP 沿 y、Lateral 沿 x);裁到螺絲 bbox 外 margin_mm 的 spine 區域;骨用 percentile(1,99) 獨立視窗,螺絲再疊加裁白。 方向:SimpleITK LPS(x→右、y→後、z→上);AP 頂=上、病人右在畫面左(R 標記); Lateral 頂=上、前位在左、後位在右(A/P 標記)。 spacing 各軸不等時先重取樣到 min(spacing) 各向同性格,維持投影 aspect ratio。 輸出 x-ap.jpg / x-lat.jpg,回傳 {view: jpg_path}。""" import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt vid = os.path.basename(os.path.normpath(out_dir)) ct = sitk.ReadImage(ct_path) cbt = sitk.ReadImage(cbt_path) if ct.GetSize() != cbt.GetSize(): raise ValueError(f'cbt/CT grid 尺寸不符 {cbt.GetSize()} vs {ct.GetSize()}') sp = np.array(ct.GetSpacing(), float) # (x,y,z) native_size = ct.GetSize() # spacing 各軸不等:先重取樣 CT/螺絲(與後面的分割 label)到 # min(spacing) 的各向同性格,維持投影视圖正確的 aspect ratio min_sp = float(sp.min()) isosp = isosize = None if not np.allclose(sp, min_sp): isosp = [min_sp, min_sp, min_sp] isosize = [max(1, int(round(s * v / min_sp))) for s, v in zip(sp, ct.GetSize())] o, d = ct.GetOrigin(), ct.GetDirection() ct = sitk.Resample(sitk.Cast(ct, sitk.sitkFloat32), isosize, sitk.Transform(), sitk.sitkLinear, o, isosp, d, 0.0) cbt = sitk.Resample(cbt, isosize, sitk.Transform(), sitk.sitkNearestNeighbor, o, isosp, d, 0) ct_arr = sitk.GetArrayFromImage(ct).astype(np.float32) # (z,y,x) cbt_arr = sitk.GetArrayFromImage(cbt) sp = np.array(ct.GetSpacing(), float) metal = cbt_arr > 0 try: _, lb_path, _ = find_native_paths(vid) lb_img = sitk.ReadImage(lb_path) # 比對「重取樣前」的 native grid(label 與原 CT 同格) if lb_img.GetSize() != native_size: raise ValueError(f'label/CT grid 尺寸不符 {lb_img.GetSize()} vs {native_size}') if isosp is not None: lb_img = sitk.Resample(lb_img, isosize, sitk.Transform(), sitk.sitkNearestNeighbor, ct.GetOrigin(), isosp, ct.GetDirection(), 0) lb = sitk.GetArrayFromImage(lb_img) spine = (lb >= 1) & (lb <= 24) # LABEL_MAP: C1..L5 全為脊椎 except Exception as e: logger.warning(f'{vid}: native 分割 label 不可用({e});' f'退回 HU 300-3000 閾值當脊椎骨') spine = (ct_arr >= 300) & (ct_arr <= 3000) bone_mu = np.where(spine & ~metal, np.clip(ct_arr, 0, 2000) / 400.0, 0.0) metal_mu = 60.0 * metal z, y, x = np.where(metal) if z.size == 0: raise ValueError(f'{vid}: cbt 無螺絲 voxel') mz, my, mx = (int(margin_mm / s) for s in (sp[2], sp[1], sp[0])) zs = slice(max(0, z.min() - mz), min(ct_arr.shape[0], z.max() + mz + 1)) ys = slice(max(0, y.min() - my), min(ct_arr.shape[1], y.max() + my + 1)) xs = slice(max(0, x.min() - mx), min(ct_arr.shape[2], x.max() + mx + 1)) proj = { 'ap': (bone_mu[zs, :, xs].sum(axis=1), metal_mu[zs, :, xs].sum(axis=1)), # 沿 y 積分 'lateral': (bone_mu[zs, ys, :].sum(axis=2), metal_mu[zs, ys, :].sum(axis=2)) # 沿 x 積分 } flip_x = {'ap': True, 'lateral': False} markers = {'ap': ('R', 'L'), 'lateral': ('A', 'P')} # 畫面左=前位(A)、右=後位(P) os.makedirs(out_dir, exist_ok=True) paths = {} for view in views: if view not in proj: continue b, m = proj[view] b = b[::-1, ::-1] if flip_x[view] else b[::-1, :] # 頂=頭端 m = m[::-1, ::-1] if flip_x[view] else m[::-1, :] bnz = b[b > 0] if bnz.size: lo, hi = np.percentile(bnz, 1), np.percentile(bnz, 99) bone = np.clip((b - lo) / (hi - lo + 1e-9), 0, 1) ** 0.7 else: bone = np.zeros_like(b) mmax = float(m.max()) metal_img = (m / (mmax + 1e-9)) ** 0.5 if mmax > 0 else m * 0 img = np.clip(bone + metal_img, 0, 1) ll, rl = markers[view] h, w = img.shape fig, ax = plt.subplots(figsize=(8.0 * w / h, 8.0), dpi=110) ax.imshow(img, cmap='gray', interpolation='nearest') ax.set_title(f'{view.upper()} projection (spine + screws) - {vid}', color='white', fontsize=13) ax.text(0.01, 0.98, ll, transform=ax.transAxes, color='cyan', fontsize=13, va='top', ha='left', fontweight='bold') ax.text(0.99, 0.98, rl, transform=ax.transAxes, color='cyan', fontsize=13, va='top', ha='right', fontweight='bold') ax.axis('off') fig.tight_layout(pad=0.5) p = os.path.join(out_dir, PROJ_FILENAME[view]) fig.savefig(p, format='jpg', facecolor='black') plt.close(fig) paths[view] = p logger.info(f'{vid}: {view} projection -> {p}') return paths def main(): parser = argparse.ArgumentParser( description='Write ///cbt.nii.gz (screws mapped to native space) ' 'from a side_results run') parser.add_argument('run_id', help='e.g. 20260907_230652') parser.add_argument('volumes', nargs='*', help='volume ids (full or trailing digits); default: all in the run') parser.add_argument('--date', default=None, help='output date dir (default: run_id[:8])') args = parser.parse_args() logging.basicConfig(level=logging.INFO, format='%(asctime)s [%(levelname)s] %(name)s: %(message)s', datefmt='%Y-%m-%d %H:%M:%S') run_dir = os.path.join(SIDE_RESULT_DIR, args.run_id) if not os.path.isdir(run_dir): sys.exit(f'side results dir not found: {run_dir}') run_vols = sorted(d for d in os.listdir(run_dir) if os.path.isdir(os.path.join(run_dir, d))) if args.volumes: vols = [v for v in run_vols if v in args.volumes or v.rsplit('.', 1)[-1] in args.volumes] if not vols: sys.exit(f'none of {args.volumes} found in run {args.run_id}') else: vols = run_vols ok, fail = 0, 0 for vid in vols: try: write_volume_cbt(vid, args.run_id, date=args.date) ok += 1 except Exception as e: fail += 1 logger.error(f'{vid}: {e}') print(f'done: {ok} written, {fail} failed / {len(vols)} volume(s)') if __name__ == '__main__': main()