docs: add todays status update presentation

Author: 404Simon

docs/update_05_19.pdf

@@ -0,0 +1,153 @@
+#set page(
+  width: 28.8cm,
+  height: 16.2cm,
+  margin: (top: 1.4cm, bottom: 1cm, left: 1.8cm, right: 1.8cm),
+  fill: white,
+  numbering: "1",
+  number-align: right,
+)
+
+#set text(font: "New Computer Modern", size: 16pt)
+#set par(justify: true, leading: 0.65em)
+
+#let accent = rgb("#1d4ed8")
+#let accent-light = rgb("#eff6ff")
+#let accent-mid = rgb("#93c5fd")
+#let muted = rgb("#6b7280")
+#let dark = rgb("#111827")
+#let green-bg = rgb("#f0fdf4")
+#let green-border = rgb("#bbf7d0")
+#let green-text = rgb("#166534")
+
+#let slide(title, body) = {
+  pagebreak()
+  block(
+    width: 100%,
+    inset: (top: 8pt, bottom: 10pt, left: 0pt, right: 0pt),
+    stroke: (bottom: 2.5pt + accent),
+  )[
+    #text(size: 24pt, fill: accent, weight: "bold")[#title]
+  ]
+  v(0.5cm)
+  body
+}
+
+#let highlight(body) = {
+  block(
+    width: 100%,
+    fill: accent-light,
+    inset: 14pt,
+    radius: 6pt,
+    stroke: 1pt + accent-mid,
+  )[
+    #body
+  ]
+}
+
+#let proofbox(body) = {
+  block(
+    width: 100%,
+    fill: green-bg,
+    inset: 14pt,
+    radius: 6pt,
+    stroke: 1pt + green-border,
+  )[
+    #body
+  ]
+}
+
+#align(center + horizon)[
+  #block(width: 80%)[
+    #align(center)[
+      #text(size: 34pt, fill: accent, weight: "bold")[
+        VesSkel\
+      ]
+      #v(1.0cm)
+      #text(size: 20pt, fill: dark)[
+        Vessel Skeletonization and Graph-Based\
+        Phenotype Analysis in Retinal Fundus Images
+      ]
+      #v(1.2cm)
+      #line(length: 40%, stroke: 1.5pt + accent)
+      #v(0.8cm)
+      #text(size: 16pt, fill: muted)[
+        Simon Wittmann
+
+        Supervisor: Anna Möller
+      ]
+      #v(0.3cm)
+      #text(size: 14pt, fill: muted)[
+        19. Mai 2026
+      ]
+    ]
+  ]
+]
+
+#slide("Implementation Progress")[
+  #v(-0.3cm)
+  - Experiment: Removing correlated features did not improve the best classifier
+  - Refactoring, better Docstrings and propagate plugin version to `napari.yaml`
+  - Unified `PipelineConfig` (JSON-serializable, shared napari + CLI)
+  - `vesskel`-CLI with `run` / `config-init` / `validate-config`
+  - Refactored napari widgets onto a single widget using shared `analyze_binary_image` pipeline
+  - Feature comparison table (REAVER, VesselVio, VesselExpress, TWOMBLI, VesSAP, Skan)
+]
+
+
+#slide("Unified Pipeline: napari + CLI")[
+  The core analysis is now a single shared function `analyze_binary_image()` used by both the napari widget and the new standalone CLI.
+
+  #v(0.3cm)
+  #highlight[
+    *CLI usage:* `vesskel run --input "data/*.png" --config config.json --out results/`
+
+    *Config management:* `vesskel config-init` (starter JSON), `vesskel validate-config` (check validity)
+  ]
+
+  #v(0.3cm)
+  *Config as contract:* same file can be exported/imported inside napari
+
+  *Current Limited Config-Options:*
+  + Branch extraction toggle, branch text labels, summary features, fractal dimension
+  + Output controls: skeleton .npy/.png, summary.csv, per-image branches.csv
+]
+
+#slide("Feature Comparison: Tools Overview")[
+  #v(-0.5cm)
+
+  See `Feature_Comparison.xlsx`
+
+  #v(0.3cm)
+  #set text(size: 14pt)
+  #highlight[
+    \* I only took features that can be e2e-extracted using the Tool, e.g. Vessap uses their DL Network, then go through Allen Cell Registration (external Tool) and then analyze the Results using Matlab code.
+  ]
+  #highlight[
+    *Vipar* is not included in the comparison: it is not an open-source package and cannot be used programmatically.
+  ]
+  #highlight[
+    *Skan* is built around powerful pandas dataframes. Features are often not directly outputted but can be easily computed, e.g. `endpoint_count	= np.sum(skel.degrees == 1)` or `min_segment_length = min(summarize()['branch_distance'])`. I treated features that can be easily computed as present.
+
+    This extensibility is a strong argument for further relying on the library.
+  ]
+]
+
+#slide("Summary & Next Steps")[
+
+  #columns(2, gutter: 1.5em)[
+    *What I did:*
+    + Unified pipeline
+    + Standalone `vesskel` CLI (`run`, `config-init`, `validate-config`)
+    + Configurable pipeline via JSON
+    + Feature comparison table across 6 other tools
+
+    #colbreak()
+
+    *Next steps:*
+    + Add more features
+    + Pipeline Performance Improvements?
+    + Group Feature Table into Categories
+    + Integrate original image for intensity-based features
+    + Add Preprocessing-Options (Clique Removal, etc.)
+  ]
+]