Patch visualization: Highlight that areas that are never sampled

Description

Contributor guide

Tech stack

python

Domain

machine learningdata

Issue type

feature

DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.

3

Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.

half day

Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.

fresh

ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.

mostly clear

Prerequisites

Understanding of patch sampling in medical imagingFamiliarity with visualization code in the repository

Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.

60

Research direction

Examine the existing thumbnail generation code in the repository (likely in the visualization module) to understand how patches are currently displayed. Identify the logic that determines which pixels are sampled for training. Modify the visualization to color unsampled pixels differently, e.g., by adding a semi transparent overlay. Review any related documentation or comments about sampling strategies to ensure accuracy.