diff --git a/atlas/templates/atlas/case_display_block.html b/atlas/templates/atlas/case_display_block.html index 58755e1a..85dbeaa9 100755 --- a/atlas/templates/atlas/case_display_block.html +++ b/atlas/templates/atlas/case_display_block.html @@ -5,7 +5,7 @@ Series {{ forloop.counter }}:
- + {{series.get_block}}
diff --git a/atlas/templates/atlas/partials/_series_split_by_tag.html b/atlas/templates/atlas/partials/_series_split_by_tag.html index 3dc3bb5e..329d0b51 100644 --- a/atlas/templates/atlas/partials/_series_split_by_tag.html +++ b/atlas/templates/atlas/partials/_series_split_by_tag.html @@ -5,9 +5,11 @@ class="btn btn-outline-warning btn-sm" hx-get="{% url 'atlas:series_split_by_tag' pk=series.pk %}?analyze=1" hx-target="#series-split-by-tag-panel" - hx-swap="outerHTML"> + hx-swap="outerHTML" + hx-indicator="#series-split-analysis-indicator"> Analyze split options + {% if analyze_requested %} @@ -16,7 +18,8 @@ action="{% url 'atlas:series_split_by_tag' pk=series.pk %}" hx-post="{% url 'atlas:series_split_by_tag' pk=series.pk %}" hx-target="#split-by-tag-result" - hx-swap="innerHTML"> + hx-swap="innerHTML" + hx-indicator="#series-split-submit-indicator"> {% csrf_token %}
@@ -99,7 +102,8 @@ action="{% url 'atlas:series_split_by_tag' pk=series.pk %}" hx-post="{% url 'atlas:series_split_by_tag' pk=series.pk %}" hx-target="#tag-consistency-split-result" - hx-swap="innerHTML"> + hx-swap="innerHTML" + hx-indicator="#tag-consistency-split-indicator"> {% csrf_token %} @@ -143,7 +147,8 @@ action="{% url 'atlas:series_split_by_tag' pk=series.pk %}" hx-post="{% url 'atlas:series_split_by_tag' pk=series.pk %}" hx-target="#tag-consistency-split-result" - hx-swap="innerHTML"> + hx-swap="innerHTML" + hx-indicator="#tag-consistency-split-indicator"> {% csrf_token %} @@ -168,6 +173,7 @@
+
diff --git a/atlas/templates/atlas/series_viewer.html b/atlas/templates/atlas/series_viewer.html index ae42753c..47a06e8a 100755 --- a/atlas/templates/atlas/series_viewer.html +++ b/atlas/templates/atlas/series_viewer.html @@ -32,7 +32,7 @@ {% with image_url_array_and_count=series.get_image_url_array_and_count %}
@@ -202,10 +202,12 @@ hx-get="{% url 'atlas:series_tag_consistency' pk=series.pk %}?analyze=1" hx-target="#series-tag-consistency-modal .modal-content" hx-swap="innerHTML" + hx-indicator="#series-tag-consistency-load-indicator" data-bs-toggle="modal" data-bs-target="#series-tag-consistency-modal"> Analyze tag consistency + {% if can_edit %}
-
-
Viewer Preview
-
-
Viewer / Compare Preview
+
+
+
+
Downsample preview comparison
+
+
-
-
Truncate Range
+
Operations
-
- -
- - +
+ {% csrf_token %} + + + +
+ +
+ + +
-
-
- -
- - +
+ +
+ + +
-
-
- -
- -
- -
-
Disk Space Optimization
-
- - - Removes DICOM files that do not contain usable image data. +
+ + +
-
- - - Reduces resolution while preserving original hash for duplicate detection. -
-
- +
+ +
+ + + Original hash is preserved after downsampling. +
+ +
+ + +
+ +
+ +
+
Generate reconstructions
+
+
+ + +
+
+ + +
+
+ + +
+
+ +
+
+ + +
+
+ + +
+
+ +
+ +
+
+
-
-
- - -
+
+ + Processing operations may take time for large stacks. + +
+
+
+
@@ -338,7 +391,7 @@ if (saved) { const viewer = document.getElementById('root'); if (viewer) { - viewer.style.minHeight = saved; + viewer.style.height = saved; } } } @@ -360,117 +413,133 @@ }); resizeObserver.observe(viewer); restoreViewerHeight(); + requestAnimationFrame(() => { + try { + if (window.resizeDicomViewers) { + window.resizeDicomViewers(); + } + window.dispatchEvent(new Event('resize')); + } catch (e) { + console.warn('Viewer resize dispatch failed', e); + } + }); } - // Modal truncate handlers + function syncOptimizeBounds() { + const startInput = document.getElementById('truncate-lower-input'); + const endInput = document.getElementById('truncate-upper-input'); + const startHidden = document.getElementById('opt-start-hidden'); + const endHidden = document.getElementById('opt-end-hidden'); + if (!startInput || !endInput || !startHidden || !endHidden) { + return; + } + startHidden.value = startInput.value; + endHidden.value = endInput.value; + } + + // Modal optimization handlers const truncateModal = document.getElementById('truncate-series-modal'); if (truncateModal) { - truncateModal.addEventListener('show.bs.modal', function() { - // Initialize the modal viewer + truncateModal.addEventListener('show.bs.modal', function () { setTimeout(() => { try { if (window.mountDicomViewers) { window.mountDicomViewers(); } + if (window.resizeDicomViewers) { + window.resizeDicomViewers(); + } } catch (e) { console.warn('Modal viewer init failed', e); } }, 200); }); + const getStackPosition = window[`getCurrentStackPosition_${apiKey}`] || window.getCurrentStackPosition_root; + document.getElementById('truncate-set-lower-btn')?.addEventListener('click', () => { - if (window.getCurrentStackPosition_root) { - const pos = window.getCurrentStackPosition_root(0) + 1; + if (getStackPosition) { + const pos = getStackPosition(0) + 1; document.getElementById('truncate-lower-input').value = pos; + syncOptimizeBounds(); } }); document.getElementById('truncate-set-upper-btn')?.addEventListener('click', () => { - if (window.getCurrentStackPosition_root) { - const pos = window.getCurrentStackPosition_root(0) + 1; + if (getStackPosition) { + const pos = getStackPosition(0) + 1; document.getElementById('truncate-upper-input').value = pos; + syncOptimizeBounds(); } }); + document.getElementById('truncate-lower-input')?.addEventListener('input', syncOptimizeBounds); + document.getElementById('truncate-upper-input')?.addEventListener('input', syncOptimizeBounds); + document.getElementById('truncate-test-modal-btn')?.addEventListener('click', () => { const lower = parseInt(document.getElementById('truncate-lower-input').value) - 1; const upper = parseInt(document.getElementById('truncate-upper-input').value) - 1; - + if (lower < 0 || upper >= totalImages || lower > upper) { alert('Invalid range. Please check your bounds.'); return; } - if (window.truncateStack_root) { - const ok = window.truncateStack_root(lower, upper); + const truncateFn = window[`truncateStack_${apiKey}`] || window.truncateStack_root; + if (truncateFn) { + const ok = truncateFn(lower, upper); if (ok) { document.getElementById('truncate-modal-output').innerHTML = `Preview shows images ${lower + 1} to ${upper + 1} (${upper - lower + 1} total).`; document.getElementById('truncate-modal-output').classList.remove('d-none'); } } }); + } - document.getElementById('truncate-execute-modal-btn')?.addEventListener('click', () => { - const lower = parseInt(document.getElementById('truncate-lower-input').value) - 1; - const upper = parseInt(document.getElementById('truncate-upper-input').value) - 1; - const removeEmpty = document.getElementById('remove-empty-dicoms-check').checked; - const downsample = document.getElementById('downsample-pixels-check').checked; + document.body.addEventListener('htmx:configRequest', function (event) { + const form = document.getElementById('series-optimize-form'); + if (!form || event.target !== form) { + return; + } + syncOptimizeBounds(); + }); - if (lower >= upper) { - alert('The lower bound must be less than the upper bound.'); + document.body.addEventListener('htmx:afterSwap', function (event) { + if (event.target && event.target.id === 'series-optimize-feedback') { + const payload = document.getElementById('downsample-compare-payload'); + if (!payload) { return; } - const totalToKeep = upper - lower + 1; - const confirmMsg = `Truncate series to ${totalToKeep} images?${removeEmpty ? '\n- Remove empty DICOMs' : ''}${downsample ? '\n- Downsample pixel data' : ''}`; - - if (confirm(confirmMsg)) { - // Build URL with optional parameters - let truncateUrl = `{% url 'atlas:series_truncate' series.pk 0 0 %}`.replace('/0/0/', `/${lower}/${upper}/`); - if (removeEmpty) truncateUrl += '?remove_empty=1'; - if (downsample) truncateUrl += (removeEmpty ? '&' : '?') + 'downsample=1'; - - htmx.ajax('GET', truncateUrl, '#truncate-modal-output'); - - // Close modal after a delay - setTimeout(() => { - const modal = bootstrap.Modal.getInstance(truncateModal); - if (modal) modal.hide(); - }, 1500); + const namedStacks = payload.dataset.namedStacks; + if (!namedStacks) { + return; } - }); - } - // Keep old inline handlers for compatibility - $("#set-lower-truncation-bound-button").click(() => { - $("#lower-truncation-bound-input").val(getCurrentStackPosition_root(0) + 1); - }); - $("#set-upper-truncation-bound-button").click(() => { - $("#upper-truncation-bound-input").val(getCurrentStackPosition_root(0) + 1); - }); - $("#truncate-test-button").click(() => { - const lower = parseInt($("#lower-truncation-bound-input").val()) - 1; - const upper = parseInt($("#upper-truncation-bound-input").val()) - 1; - const ok = window[`truncateStack_${apiKey}`](lower, upper); - if (ok) { - $("#truncate-output").text("The truncated images are shown above."); + const compareWrap = document.getElementById('downsample-compare-wrap'); + const compareViewer = document.getElementById('downsample-compare-viewer'); + if (!compareWrap || !compareViewer) { + return; + } + + compareWrap.classList.remove('d-none'); + compareViewer.dataset.namedStacks = namedStacks; + compareViewer.dataset.autoCacheStack = 'false'; + + try { + if (window.mountDicomViewers) { + window.mountDicomViewers(); + } + if (window.resizeDicomViewers) { + window.resizeDicomViewers(); + } + } catch (err) { + console.warn('Failed to mount downsample compare viewer', err); + } } }); - $("#truncate-button").click(() => { - lower_bound = parseInt($("#lower-truncation-bound-input").val()) - 1; - upper_bound = parseInt($("#upper-truncation-bound-input").val()) - 1; - if (lower_bound >= upper_bound) { - alert("The lower bound must be less than the upper bound."); - return; - } - - if(confirm(`Truncated series. This will leave ${upper_bound - lower_bound + 1} images.`) == true) { - const truncateTemplate = `{% url 'atlas:series_truncate' series.id 0 0 %}`; // e.g. /atlas/series/920/truncate/0/0/ - const truncateUrl = truncateTemplate.replace('/0/0/', `/${lower_bound}/${upper_bound}/`); - htmx.ajax("GET", truncateUrl, "#truncate-output") - } - }) + syncOptimizeBounds(); $("#add-finding-button").click(() => { $("#hidden-form").show() diff --git a/atlas/urls.py b/atlas/urls.py index 2bc13a22..80e1047e 100755 --- a/atlas/urls.py +++ b/atlas/urls.py @@ -565,6 +565,11 @@ urlpatterns = [ views.series_image_size_htmx, name="series_image_size", ), + path( + "series//optimize/", + views.series_optimize_htmx, + name="series_optimize", + ), path("series//images/", views.series_images_partial, name="series_images"), path("series//authors", views.SeriesAuthorUpdate.as_view(), name="series_authors"), path("series//finding/related", views.series_finding_related, name="series_finding_related"), diff --git a/atlas/views.py b/atlas/views.py index 6eb11027..85887793 100755 --- a/atlas/views.py +++ b/atlas/views.py @@ -2,6 +2,8 @@ import json import pprint import csv import random +import copy +import io from typing import Any from dal import autocomplete from django.db.models.base import Model as Model @@ -217,9 +219,7 @@ def series_truncate_htmx(request, series_id, start, end): """HTMX endpoint to truncate a series' images to the given inclusive start/end bounds (zero-based). Returns an HTML fragment with the result. - Query parameters: - - remove_empty: Remove DICOMs with no content (all pixels zero) - - downsample: Downsample pixel data by 50% while preserving original hash + This endpoint only performs truncation for backward compatibility. """ series = get_object_or_404(Series, pk=series_id) @@ -227,61 +227,18 @@ def series_truncate_htmx(request, series_id, start, end): return HttpResponse("
Permission denied
") images_removed = [] - images_downsampled = [] - remove_empty_dicoms = request.GET.get('remove_empty') in ('1', 'true', 'True') - downsample_pixels = request.GET.get('downsample') in ('1', 'true', 'True') - + for n, image in enumerate(series.get_images()): if n >= int(start) and n <= int(end): - # Keep images within bounds - if remove_empty_dicoms and image.image: - try: - # Check if DICOM is effectively empty (all zeros) - import pydicom - from io import BytesIO - dcm = pydicom.dcmread(BytesIO(image.image.read())) - if hasattr(dcm, 'pixel_array'): - px_array = dcm.pixel_array - # If all pixels are zero, mark for removal - if (px_array == 0).all(): - image.removed = True - image.image = None - image.save() - images_removed.append(image.pk) - continue - except Exception as e: - logger.warning(f"Could not analyze DICOM {image.pk}: {e}") - - if downsample_pixels and image.image: - try: - # Downsample pixel data (reduce resolution by 50%) - import pydicom - import numpy as np - from io import BytesIO - - dcm = pydicom.dcmread(BytesIO(image.image.read())) - if hasattr(dcm, 'pixel_array'): - original_array = dcm.pixel_array - # Downsample: take every other pixel in each dimension - downsampled = original_array[::2, ::2] if original_array.ndim == 2 else original_array[:, ::2, ::2] - dcm.pixel_array[:] = downsampled - - # Save back to image field - output = BytesIO() - dcm.save_as(output, write_like_original=False) - output.seek(0) - image.image.save(f'dicom_{image.pk}.dcm', output, save=True) - images_downsampled.append(image.pk) - except Exception as e: - logger.warning(f"Could not downsample DICOM {image.pk}: {e}") - continue - else: - # Remove images outside bounds - image.removed = True - image.image = None - image.save() - images_removed.append(image.pk) + + image.removed = True + image.image = None + image.save() + images_removed.append(image.pk) + + series.modified = Series.SeriesModifiedChocies.TR + series.save(update_fields=["modified"]) # Recalculate stored series size try: @@ -295,16 +252,340 @@ def series_truncate_htmx(request, series_id, start, end): "atlas/partials/truncate_result.html", { "images_removed": images_removed, - "images_downsampled": images_downsampled, + "images_downsampled": [], "series": series, - "remove_empty_dicoms": remove_empty_dicoms, - "downsample_pixels": downsample_pixels, + "remove_empty_dicoms": False, + "downsample_pixels": False, }, request=request, ) return HttpResponse(html) +def _read_series_image_dataset(series_image): + if not series_image.image: + return None + + try: + series_image.image.open("rb") + series_image.image.seek(0) + return pydicom.dcmread(series_image.image, force=True) + except Exception as exc: + logger.warning("Failed to read DICOM for image {}: {}", series_image.pk, exc) + return None + + +def _is_empty_dicom(ds): + try: + px = ds.pixel_array + return bool((px == 0).all()) + except Exception: + return False + + +def _resize_array_nearest(arr, target_rows, target_cols): + import numpy as np + + rows, cols = arr.shape[0], arr.shape[1] + row_idx = np.clip(np.round(np.linspace(0, rows - 1, target_rows)).astype(int), 0, rows - 1) + col_idx = np.clip(np.round(np.linspace(0, cols - 1, target_cols)).astype(int), 0, cols - 1) + return arr[np.ix_(row_idx, col_idx)] + + +def _downsample_dicom_dataset(ds, reduction_pct): + if reduction_pct <= 0 or reduction_pct >= 100: + raise ValueError("Downsample percentage must be between 1 and 99") + + factor = (100 - reduction_pct) / 100.0 + px = ds.pixel_array + + if px.ndim != 2: + raise ValueError("Only 2D DICOM slices are supported for this downsample operation") + + target_rows = max(1, int(round(px.shape[0] * factor))) + target_cols = max(1, int(round(px.shape[1] * factor))) + resized = _resize_array_nearest(px, target_rows, target_cols) + + ds.Rows = int(target_rows) + ds.Columns = int(target_cols) + ds.PixelData = resized.tobytes() + ds.pop("SmallestImagePixelValue", None) + ds.pop("LargestImagePixelValue", None) + return ds + + +def _create_series_derivative(source_series, description_suffix): + derived = Series.objects.get(pk=source_series.pk) + derived.pk = None + derived.id = None + derived.series_instance_uid = generate_uid() + derived.description = f"{source_series.description or 'Series'} [{description_suffix}]" + derived.modified = Series.SeriesModifiedChocies.RE + derived.save() + derived.case.set(source_series.case.all()) + derived.author.set(source_series.author.all()) + return derived + + +def _series_image_urls_json(series): + image_url_array_and_count = series.get_image_url_array_and_count() + try: + urls = json.loads(image_url_array_and_count[0]) + except Exception: + urls = [] + return urls + + +@login_required +@require_http_methods(["POST"]) +def series_optimize_htmx(request, series_id): + """Run disk optimization operations for a series. + + Scope: Series editors only. + + Supported operations: + - remove_empty + - downsample + - downsample_preview + - reconstruct + - truncate + """ + series = get_object_or_404(Series, pk=series_id) + + if not series.check_user_can_edit(request.user): + return HttpResponse('
Permission denied
') + + operation = request.POST.get("operation", "").strip() + start = int(request.POST.get("start", "1") or 1) - 1 + end = int(request.POST.get("end", str(series.get_image_count())) or series.get_image_count()) - 1 + + if end < start: + return HttpResponse('
Start must be less than or equal to end.
') + + images = list(series.get_images()) + bounded_images = [img for idx, img in enumerate(images) if idx >= start and idx <= end] + + if operation == "truncate": + removed = [] + for idx, image in enumerate(images): + if idx < start or idx > end: + image.removed = True + image.image = None + image.save() + removed.append(image.pk) + + series.modified = Series.SeriesModifiedChocies.TR + series.save(update_fields=["modified"]) + return HttpResponse( + f'
Truncate complete. Removed {len(removed)} images.
' + ) + + if operation == "remove_empty": + removed = [] + for image in bounded_images: + ds = _read_series_image_dataset(image) + if ds is None: + continue + if _is_empty_dicom(ds): + image.removed = True + image.image = None + image.save() + removed.append(image.pk) + + if removed: + series.modified = Series.SeriesModifiedChocies.TR + series.save(update_fields=["modified"]) + + return HttpResponse( + f'
Empty DICOM removal complete. Removed {len(removed)} empty images.
' + ) + + if operation in ("downsample", "downsample_preview"): + downsample_pct = int(request.POST.get("downsample_pct", "50") or 50) + + if operation == "downsample_preview": + preview_series = _create_series_derivative(series, f"Downsample preview {downsample_pct}%") + created = 0 + + for image in bounded_images: + ds = _read_series_image_dataset(image) + if ds is None: + continue + + try: + ds_out = _downsample_dicom_dataset(ds, downsample_pct) + except Exception as exc: + logger.warning("Downsample preview failed for image {}: {}", image.pk, exc) + continue + + out_io = io.BytesIO() + ds_out.save_as(out_io, write_like_original=False) + out_io.seek(0) + + new_image = SeriesImage(series=preview_series, position=image.position, upload_filename=image.upload_filename) + new_image.image.save( + f"preview_ds_{downsample_pct}_{image.pk}.dcm", + ContentFile(out_io.getvalue()), + save=False, + ) + new_image.save() + created += 1 + + original_urls = _series_image_urls_json(series) + preview_urls = _series_image_urls_json(preview_series) + named_stacks = json.dumps( + { + "Original": original_urls, + f"Preview {downsample_pct}%": preview_urls, + } + ) + escaped_named_stacks = escape(named_stacks) + + return HttpResponse( + ( + '
' + f'Downsample preview series created with {created} images. ' + f'Open preview series.' + '
' + f'
' + ) + ) + + downsampled = [] + for image in bounded_images: + ds = _read_series_image_dataset(image) + if ds is None: + continue + + try: + original_hash = image.image_blake3_hash + ds_out = _downsample_dicom_dataset(ds, downsample_pct) + out_io = io.BytesIO() + ds_out.save_as(out_io, write_like_original=False) + out_io.seek(0) + + image.image.save( + f"downsample_{downsample_pct}_{image.pk}.dcm", + ContentFile(out_io.getvalue()), + save=False, + ) + # Preserve original hash for duplicate detection continuity. + image.image_blake3_hash = original_hash + image.save(update_fields=["image", "image_blake3_hash"]) + downsampled.append(image.pk) + except Exception as exc: + logger.warning("Downsample failed for image {}: {}", image.pk, exc) + + if downsampled: + series.modified = Series.SeriesModifiedChocies.RE + series.save(update_fields=["modified"]) + + return HttpResponse( + f'
Downsample complete ({downsample_pct}%). Updated {len(downsampled)} images while preserving original hashes.
' + ) + + if operation == "reconstruct": + recon_planes = request.POST.getlist("recon_planes") + if not recon_planes: + return HttpResponse('
Select at least one reconstruction plane.
') + + slice_thickness = request.POST.get("recon_slice_thickness", "") + slice_spacing = request.POST.get("recon_slice_spacing", "") + + try: + slice_thickness_val = float(slice_thickness) if slice_thickness else None + slice_spacing_val = float(slice_spacing) if slice_spacing else None + except ValueError: + return HttpResponse('
Slice thickness and spacing must be numeric values.
') + + dicom_items = [] + for image in bounded_images: + ds = _read_series_image_dataset(image) + if ds is None: + continue + try: + arr = ds.pixel_array + if arr.ndim != 2: + continue + dicom_items.append((image, ds, arr)) + except Exception: + continue + + if len(dicom_items) < 2: + return HttpResponse('
Need at least 2 valid DICOM images in range for reconstruction.
') + + import numpy as np + + base_shape = dicom_items[0][2].shape + dicom_items = [item for item in dicom_items if item[2].shape == base_shape] + if len(dicom_items) < 2: + return HttpResponse('
Not enough consistently-sized slices for reconstruction.
') + + volume = np.stack([item[2] for item in dicom_items], axis=0) + template_ds = dicom_items[0][1] + created_series = [] + + for plane in recon_planes: + plane_norm = plane.lower() + if plane_norm == "axial": + recon_slices = [volume[i, :, :] for i in range(volume.shape[0])] + elif plane_norm == "coronal": + recon_slices = [volume[:, i, :] for i in range(volume.shape[1])] + elif plane_norm == "sagittal": + recon_slices = [volume[:, :, i] for i in range(volume.shape[2])] + else: + continue + + recon_series = _create_series_derivative(series, f"Recon {plane_norm.title()}") + recon_series.series_instance_uid = generate_uid() + recon_series.save(update_fields=["series_instance_uid"]) + + for idx, arr2d in enumerate(recon_slices): + ds_new = copy.deepcopy(template_ds) + arr2d = np.asarray(arr2d, dtype=dicom_items[0][2].dtype) + + ds_new.Rows = int(arr2d.shape[0]) + ds_new.Columns = int(arr2d.shape[1]) + ds_new.InstanceNumber = idx + 1 + ds_new.SOPInstanceUID = generate_uid() + ds_new.SeriesInstanceUID = recon_series.series_instance_uid + ds_new.PixelData = arr2d.tobytes() + + if slice_thickness_val is not None: + ds_new.SliceThickness = slice_thickness_val + if slice_spacing_val is not None: + ds_new.SpacingBetweenSlices = slice_spacing_val + + out_io = io.BytesIO() + ds_new.save_as(out_io, write_like_original=False) + out_io.seek(0) + + recon_image = SeriesImage(series=recon_series, position=idx + 1, upload_filename=f"recon_{plane_norm}_{idx+1}.dcm") + recon_image.image.save( + f"recon_{plane_norm}_{recon_series.pk}_{idx+1}.dcm", + ContentFile(out_io.getvalue()), + save=False, + ) + recon_image.save() + + created_series.append(recon_series) + + if not created_series: + return HttpResponse('
No reconstruction plane could be generated.
') + + links = " ".join( + [ + f'{escape(s.description or str(s.pk))}' + for s in created_series + ] + ) + return HttpResponse( + f'
Created {len(created_series)} reconstruction series: {links}
' + ) + + return HttpResponse('
Unknown optimize operation.
') + + @login_required def series_image_size_htmx(request, series_id): """HTMX endpoint returning the total size of images in a series.