Welcome to Scalpscan.AI
ScalpScan.AI accurately measures the hair transplant area.
With ScalpScan.AI installed on your cell phone, you will be able to do all that: to scan your patient's head, generate the 3D model, mark the bald parts and thus obtain the area, and with the help of the PRECISE scale calculate the amount of FUs per region.
Androgenetic alopecia (AGA) is a common genetic condition that affects both men and women, and it is characterized by the progressive loss of hair. Traditional AGA scales and classification methods often rely on qualitative assessments, which can be subjective and may not provide a comprehensive understanding of the condition. The subjective nature of these classifications can result in different professionals assigning different classes to the same patient using the same scale. Furthermore, such classifications have limitations in terms of detailed description, practicality for clinical assessment, and reproducibility.
To overcome these limitations, there is a need for more comprehensive and quantitative approaches to AGA classification. Incorporating objective measures, such as hair density measurements, miniaturization analysis, or 3D scalp imaging, can provide a more accurate assessment of the extent and severity of hair loss. As well as the introduction of a more quantitative and mathematical classification system can help minimize such disagreements and provide a more objective assessment of AGA. By incorporating quantitative measurements, such as accurately measuring the area to be implanted, surgeons can improve their surgical planning and enhance the outcomes of hair transplantation procedures.
For professionals who are new to the field of hair restoration, a quantitative classification can provide them with more precise guidance and improve their decision- making.
By having access to more detailed information about the extent and pattern of hair loss, they can fine-tune their surgical strategies and optimize the results of hair restoration procedures.
To close this gap, Dr. Felipe Pittella and
collaborators developed the PRECISE scale. The quantitative classification
provided by the PRECISE scale aims to address the limitations of
traditional qualitative scales in classifying and planning hair
transplant procedures for androgenetic alopecia (AGA).
By providing a more precise and quantitative assessment of Male-Pattern hair loss (MPHL), the PRECISE scale can help in accurately defining the extent and severity of baldness. This allows for a more tailored approach to hair transplant planning, ensuring that the appropriate number of follicular units (FUs) is considered for each specific case.
The reduction of distortions inherent in qualitative scales is an important aspect of the PRECISE scale. Traditional qualitative scales may not always account for variations in the distribution and density of hair loss, potentially leading to suboptimal outcomes if the same surgical strategy is applied to patients with different levels of baldness. By quantifying the classification, the PRECISE scale helps to minimize these discrepancies and provides a more accurate basis for surgical planning.
Now imagine, if you could do this using only your cell phone? With ScalpScan.AI you can do just that. A rendered 3D model of a patient's head can be utilized to measure the relative bald area (RBA) by analyzing the 3D mesh created using technologies like LiDAR/TrueDepth or similar ones.
The 3D mesh represents the surface of objects captured by scanning the environment using laser beams, infrared sensors, and cameras present in a cell phone or other devices. These technologies allow for precise capturing of the patient's head characteristics, including the topography of the bald area and its variations compared to the rest of the scalp. By analyzing the generated 3D mesh, the application can accurately measure and quantify the bald area relative to other areas of the scalp.
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