SYSTEM AND METHOD FOR SELECTING FOLLICULAR UNITS FOR HARVESTING

• US 20090306680A1
• Filed: 06/04/2008
• Published: 12/10/2009
• Est. Priority Date: 06/04/2008
• Status: Active Grant

• Current Assignee: Venus Concept, Inc.
• Original Assignee: Restoration Robotics, Inc. (Venus Concept, Inc.)
• Inventors: Liu, Hongze, Qureshi, Shehrzad A.
• Granted Patent: US 9,107,697 B2
• Time in Patent Office: Days
• US Class Current: 606/133
• CPC Class Codes: A61B 2017/00752 Hair removal or transplantation
• CPC Class Codes: A61B 2090/371 with simultaneous use of two cameras
• CPC Class Codes: A61B 34/10 Computer-aided planning, simulation or modelling of surgical operations
• CPC Class Codes: A61B 34/70 Manipulators specially adapted for use in surgery
• CPC Class Codes: A61B 90/361 Image-producing devices, e.g. surgical cameras
• CPC Class Codes: A61F 2/10 Hair or skin implants

Abstract

A system and method for selecting follicular units for hair harvesting using imaging and processing techniques are provided. The method of selecting an order of harvesting follicular units is based on a combination of one or more policies and filters that are generally designed to improve a speed, quality and efficacy of the harvesting process. The method of the present invention may be implemented with various hair harvesting and transplantation systems, including manual, partially automated and fully automated systems.

Claims

1-27. -27. (canceled)

28. A method of selecting an order of harvesting follicular units, comprising:

automatically soiling a pool of candidate follicular units based on one or more policy designed to improve one or more of speed, quality and efficacy of the hair harvesting; and

automatically selecting among those automatically sorted a particular follicular unit to be harvested next, wherein a selected follicular unit is one of the best available follicular units according to one or more additional policy.

29. The method of claim 28, further comprising automatically filtering follicular units based on a predetermined criterion.

30. The method of claim 29, wherein automatically selecting the particular follicular unit is based on a combination of a plurality of filters and policies.

31. The method of claim 28, further comprising identifying the pool of candidate follicular units for harvesting in one or more images of a surface containing follicular units;

and wherein automatically sorting comprises keeping only those follicular units that have consistently appeared in the one or more images in a predetermined preceding time interval.

32. The method of claim 28, further comprising harvesting the selected follicular unit.

33. The method of claim 28, wherein the steps of automatically sorting and selecting are continuously repeated.

34. The method of claim 28, wherein the one or more policy, or the one or more additional policy comprises 1) discarding follicular units that are located within a certain minimum distance to an item comprising one or more of another follicular unit, an edge of the field of view of the image, and a location containing blood;

or

     2) keeping follicular units that are located outside a certain minimum distance to an item comprising one or more of another follicular unit, an edge of the field of view of the image, and a location containing blood.

35. The method of claim 34, wherein the location containing blood is determined using a variance filter.

36. The method of claim 28, wherein the one or more policy, or one or more additional policy comprises 1) discarding follicular units that are less than a predetermined width, or 2) keeping follicular units that are equal or more than a predetermined width.

37. The method of claim 28, wherein the one or more policy, or one or more additional policy comprises 1) discarding follicular units that do not meet a predetermined criteria based on a number of hairs in the follicular units;

or

     2) keeping follicular units that meet a predetermined criteria based on a number of hairs in the follicular units.

38. The method of claim 28, wherein one or more policy, or one or more additional policy comprises discarding follicular units possessing a complex shape or keeping follicular units possessing a simple shape.

39. The method of claim 28, wherein automatically selecting follicular units comprises scoring follicular units based on a weighted sum of variables comprising one or more of follicular unit type, follicular unit distance to a harvesting tool, follicular unit orientation relative to an orientation of a harvesting tool, follicular unit emergence angle from a body surface, and simplicity of a shape of follicular unit.

40. The method of claim 28, wherein automatically sorting follicular units comprises skipping every Nth follicular unit in the pool of candidate follicular units.

41. The method of claim 40, comprising a skipping pattern chosen from one or more planning templates.

42. The method of claim 41, wherein a skipping pattern comprises one or both unidirectional and linear template of selecting every N^th follicle in a hair-line.

43. The method of claim 41, wherein the skipping pattern comprises a multidirectional template of selecting every N^th follicle in a patch or cluster of follicular units.

44. A method of selecting an order of harvesting follicular units using a robotic hair transplantation system, comprising:

automatically sorting a pool of candidate follicular units based on one or more policy designed to improve one or more of speed, quality and efficacy of the hair harvesting; and

automatically selecting among those automatically sorted a particular follicular unit to be harvested next, wherein a selected follicular unit is one of the best available follicular units according to one or more additional policy; and

maneuvering a robotic arm of a robotic system to place a hair harvesting tool operatively connected to the robotic arm next to the selected follicular unit to be harvested.

45. The method of claim 44, further comprising automatically filtering follicular units from the pool of candidate follicular units based on a predetermined criterion.

46. The method of claim 45, wherein a combination of the filtering criterion and one or more policy, or additional policy, comprises proximity to blood on a surface, a preference of the follicular units comprising one or more of follicular units located within a minimum distance to a hair harvesting tool, and follicular units whose orientation matches the orientation of a follicular unit that has been harvested immediately prior to the current selection.

47. The method of claim 44, wherein automatically selecting follicular units comprises scoring follicular units based on a weighted sum of variables comprising one or more of follicular unit type, follicular unit distance to a harvesting tool, follicular unit orientation relative to an orientation of a harvesting tool, follicular unit emergence angle from a body surface, and simplicity of a shape of follicular unit.

48. A system for selecting follicular units for harvesting, comprising:

an image processor, the image processor comprising instructions for;

identifying a pool of candidate follicular units for harvesting in one or more images obtained from an image acquisition device;

sorting follicular units in the pool of candidate follicular units based on one or more policies; and

selecting a particular follicular unit to be harvested next, wherein a selected follicular unit is one of the best available follicular units according to one or more additional policy.

49. The system of claim 48, further comprising a memory operatively associated with the processor.

50. The system of claim 48, further comprising an image acquisition device wherein the image acquisition device comprises at least one camera.

51. The system of claim 48, wherein the image processor is a personal computer.

52. The system of claim 48, wherein the system is a robotic system and it further comprises a robotic arm.

53. An article of manufacture comprising a machine-accessible medium including data that, when accessed by a machine, cause the machine to perform operations, comprising:

identifying a pool of candidate follicular units for harvesting in one or more images obtained from an image acquisition device;

automatically sorting follicular units in the pool of candidate follicular units based on one or more policy designed to improve one or more of speed, quality and efficacy of the hair harvesting; and

automatically selecting a particular follicular unit to be harvested next, wherein a selected follicular unit is one of the best available follicular units based on the at least one or more additional policy.