OpenDermとは？皮膚を3Dマップ化するオープンソースの撮像ロボット

OpenDerm is an open-source robotic imaging system for creating high-resolution, reproducible 3D maps of the skin. Registered scans help reveal new lesions and identify subtle changes in existing ones. ／ The hardware designs, software, and build documentation are all openly available. ／ Designed and built by Marion Lepert. ／ Not a medical device · Research use only — 概要、公開範囲、製作者、および用途の限定に関する記述より

OpenDerm captures skin at 78 pixels per millimeter, resolving details such as a mole’s pigment network and nearby individual hairs. ／ OpenDerm captures skin at 78 pixels per millimeter using less than $8,500 in hardware. It is fully open source and provides some of the highest-resolution imaging available at a fraction of the cost of commercial total-body photography systems. — 撮影解像度、費用、および市販の全身撮影システムとの比較に関する記述より

OpenDerm is built primarily from off-the-shelf parts. ／ The gantry moves the camera through four degrees of freedom. Three linear axes position the sensor head within the workspace: X travels along the side rails, Y moves across the top beam, and Z sets the camera height. A rotary axis (RX) tilts the sensor head to align the camera with the skin surface. ／ The sensor head carries a Canon EOS R7 with an RF 100 mm macro lens, a Godox MF-R76 ring flash fitted with a cross-polarization filter that reduces specular glare, and two downward-facing laser distance sensors. The distance measurements allow the control system to maintain a consistent working distance and camera orientation relative to the skin. ／ At each imaging station, the robot uses two laser sensors to control the camera’s angle and working distance before capturing a high-resolution photograph. The complete pipeline then aligns the overlapping images and reconstructs them as one continuous surface. ／ By moving close to the body and following its contours, the system can maintain consistent distance, angle, focus, and lighting while capturing high-resolution images across the skin surface. Using a single camera with cheap actuators also reduces hardware cost compared with a large array of fixed cameras. — 市販部品を中心とした構成、4つの自由度、センサーヘッドの中身、撮影の流れ、およびロボット方式を選んだ理由に関する記述より

Total-body photography remains an emerging field, with limited clinical availability in the United States and many systems still experimental or under development. ／ A high-resolution camera mounted on a robotic arm or gantry moves close to the skin and systematically across the body while maintaining a controlled distance and viewing angle. Imaging the skin region by region allows a single camera to capture much finer detail than a distant wide-field system, while requiring less space and camera hardware. The trade-off is speed: the body must be scanned sequentially rather than all at once. ／ SecondsWide-field detail$$$ ／ Examples: Neko · Canfield VECTRA · DermSpectra · FotoFinder ／ MinutesHigh-resolution detail$$ ／ Examples: SquareMind · iToBoS · OpenDerm ／ ManualVariable detailNo dedicated hardware$ ／ Examples: SkinIO · MoleMap · Miiskin — この分野の現状、近接ロボット走査方式の特徴と代償、および3つの方式のカードに記された速度・詳細さ・費用・例に関する記述より

More than 100,000 Americans are diagnosed with melanoma each year. This form of skin cancer has a five-year relative survival rate of nearly 100% when detected early, but about 34% after it reaches distant parts of the body. ／ Approximately 30% of melanomas develop within an existing mole, while 70% appear as new lesions. ／ In either case, the earliest visible sign may be small: a millimeter-scale change at the edge of a mole, a localized shift in its color or structure, or a new spot only a few millimeters across. Detecting changes at this scale requires a precise record of the skin’s prior appearance. ／ Improving total-body imaging requires progress in three areas: ／ Higher Resolution Imaging ／ Many existing total-body photography systems use wide fields of view to capture large areas of skin, but at the expense of fine detail. ／ Longitudinal datasets ／ Frequent, accessible scanning — 米国のメラノーマの数値、最初に見える兆候の小ささ、および改善が必要とされる3領域に関する記述より

Most AI models for skin-cancer detection are trained on isolated images of lesions already identified as suspicious. These datasets therefore provide little evidence of how melanomas first emerge and evolve before drawing clinical attention. Training models to recognize earlier signs of melanoma will require repeated, high-resolution images of the same skin over time. ／ Total-body photography must become more affordable and widely available. Patients at high risk should be able to receive frequent, standardized scans. — 既存の学習データセットの限界、必要とされるデータの性質、および普及の必要性に関する記述より

The complete bill of materials, CAD assembly, electrical and safety schematics, and step-by-step build instructions are publicly available. ／ OpenDerm software is available under the MIT License. The hardware design files, schematics, bill of materials, and build documentation are available under the CERN Open Hardware Licence Version 2 - Permissive (CERN-OHL-P-2.0). ／ Not a medical device · Research use only — 公開されている資料の範囲、ソフトウェアとハードウェアそれぞれのライセンス、および用途の限定に関する記述より